Podcasts about senior data scientist

Thank you to the folks at Sustain (https://sustainoss.org/) for providing the hosting account for CHAOSSCast! CHAOSScast – Episode 109 In this episode of CHAOSScast, host Georg Link is joined by Cali Dolfi, Senior Data Scientist at Red Hat, and Brittany Istenes, FINOS Ambassador. The discussion delves into the importance of measuring open source community health and the role of Software Bill of Materials (SBOM) in ensuring software security and compliance. They talk about the rising threats in open source software, the need for standardizing SBOMs, and how organizations can leverage these tools to proactively manage risks and project health. Also, they touch on practical steps being taken at Red Hat and other organizations to address these challenges. Hit download now to hear more! [00:00:21] Our guests introduce themselves and their backgrounds. [00:01:55] Georg explains the rise of malicious packages (700%) and the risks of neglected open source components. [00:04:36] What is a SBOM? Brittany explains SBOMs as a list of all software components and libraries in each application and automation and tooling adoption is discussed. [00:06:08] Cali outlines the lack of consensus on SBOM fields and formats and advocates for including upstream repo links to assess project health. Brittany mentions companies being cautious about publicizing SBOMs due to IP concerns. [00:09:12] Georg gives a historical overview about SBOMs began as tools for license compliance and how SBOMs now cover more including cybersecurity, post U.S. Executive Order 14028 (May 2021). [00:15:51] Georg shares three pillars of SBOM strategy: License compliance, Security, and Project Health and how CHAOSS Metrics can be combined with SBOMs to move from reactive to proactive strategies. [00:16:59] Brittany emphasizes risk analysis and good design from project inception and proactive open source strategies save effort later. [00:18:43] Cali talks about using project health metrics and advocates for tracking maintainer activity, patch frequency, and project responsiveness. [00:21:28] Brittany stresses internal engineering education on project health and risk and developer smush understand what makes a project “healthy.” [00:22:55] Georg talks about how open source has evolved and details using CHAOSS metrics for risk assessment and CI/CD integration. [00:27:36] Cali shares Red Hat's efforts to define what makes a project vulnerable and how it's focused on detecting and sunsetting unmaintained dependencies. [00:31:37] Brittany emphasizes risk from version mismatches and misinterpreted CVEs and mentions a CHAOSS doc to read, “Metrics for OSS Viability” by Gary White. [00:34:17] We end with Georg sharing some upcoming events: CHAOSScon North America, June 26 and Open Source Summit North America, June 23-25. Value Adds (Picks) of the week: [00:36:08] Georg's pick is building a platform for his dog to look out the window. [00:37:06] Brittany's pick is spending time with Georg and Cali. [00:38:12] Cali's pick is her great support system since having ACL surgery. *Panelist: * Georg Link Guests: Cali Dolfi Brittany Istenes Links: CHAOSS (https://chaoss.community/) CHAOSS Project X (https://twitter.com/chaossproj?lang=en) CHAOSScast Podcast (https://podcast.chaoss.community/) podcast@chaoss.community (mailto:podcast@chaoss.community) Georg Link Website (https://georg.link/) Britany Istenes LinkedIn (https://www.linkedin.com/in/brittany-istenes-91b902152/) Brittany Istenes GitHub (https://github.com/BrittanyIstenes) Cali Dolfi LinkedIn (https://www.linkedin.com/in/calidolfi/) State of the Software Supply Chain (Sonatype) (https://www.sonatype.com/state-of-the-software-supply-chain/introduction) CHAOSScast Podcast-Episode 103: GrimoireLab at FreeBSD (https://podcast.chaoss.community/103) CHAOSS Community: Metrics for OSS Viability by Gary White (https://chaoss.community/viability-metrics-what-its-made-of/) CHAOSScon North America 2025, Denver, CO, June 26 (https://chaoss.community/chaosscon-2025-na/) Open Source Summit North America, Denver CO, June 23-25 (https://events.linuxfoundation.org/open-source-summit-north-america/) Fintech Open Source (FINOS) (https://www.finos.org/) Cyber Resilience Act (European Commission) (https://digital-strategy.ec.europa.eu/en/policies/cyber-resilience-act) Rising Threat: Understanding Software Supply Chain Cyberattacks And Protecting Against Them(Forbes) (https://www.forbes.com/councils/forbestechcouncil/2024/02/06/rising-threat-understanding-software-supply-chain-cyberattacks-and-protecting-against-them/) Executive Order on Strengthening and Promoting Innovation in the Nation's Cybersecurity (The White House) (https://bidenwhitehouse.archives.gov/briefing-room/presidential-actions/2025/01/16/executive-order-on-strengthening-and-promoting-innovation-in-the-nations-cybersecurity/) Types of Software Bill of Material (SBOM) Documents (https://www.cisa.gov/sites/default/files/2023-04/sbom-types-document-508c.pdf) OpenSSF Scorecard (https://openssf.org/projects/scorecard/) OSS Project Viability Starter (CHAOSS) (https://chaoss.community/kb/metrics-model-project-viability-starter/) Show Me What You Got: Turning SBOMs Into Actions- Georg Link & Brittany Istenes (https://lfms25.sched.com/event/1urWz) Special Guests: Brittany Istenes and Cali Dolfi.

V novej epizóde relácie Trendy v biznise hovorí Peter Bakonyi, Senior Data Scientist spoločnosti Aliter Technologies, o tom, ako AI reálne funguje v slovenských podnikoch, aké sú jej výhody, riziká a čo všetko treba splniť, aby sa z nej stala konkurenčná výhoda. Článok vznikol v rámci seriálu We Know How v spolupráci s komerčným partnerom.

The Times Higher Education recently reported that Bluesky has overtaken X in hosting posts related to new academic research. And yet many Medical Affairs teams aren't equipped to maximize the potential of this emerging resources. Here we speak with Mike Taylor, Head of Data Insights, at Altmetric, and Carlos Areia, Senior Data Scientist at Altmetric about the uses of Bluesky in comparison with exiting social media platforms, and how Medical Affairs can leverage this resource for insights, KOL identification/mapping, data dissemination and more. 

Believe it or not, the field of Kardashian studies can inform the ways Medical Affair professionals identify and understand influencers and influence in the space of science communications. Here we talk with Mike Taylor, Head of Data Insights at Altmetric, and Carlos Areia, Senior Data Scientist at Altmetric about making sense of what is otherwise certainly nonsense. 

Asteroid mining is making a comeback. It may sound futuristic, but some startups are betting on a viable and economic path to making it a reality and investors are taking notice. One of those companies is Karman+, and this week, I'm joined by its Co-Founder, Daynan Crull. Enjoy!  

NVIDIA RAPIDS is an open-source suite of GPU-accelerated data science and AI libraries. It leverages CUDA and significantly enhances the performance of core Python frameworks including Polars, pandas, scikit-learn and NetworkX. Chris Deotte is a Senior Data Scientist at NVIDIA and Jean-Francois Puget is the Director and a Distinguished Engineer at NVIDIA. Chris and Jean-Francois The post NVIDIA RAPIDS and Open Source ML Acceleration with Chris Deotte and Jean-Francois Puget appeared first on Software Engineering Daily.

NVIDIA RAPIDS is an open-source suite of GPU-accelerated data science and AI libraries. It leverages CUDA and significantly enhances the performance of core Python frameworks including Polars, pandas, scikit-learn and NetworkX. Chris Deotte is a Senior Data Scientist at NVIDIA and Jean-Francois Puget is the Director and a Distinguished Engineer at NVIDIA. Chris and Jean-Francois The post NVIDIA RAPIDS and Open Source ML Acceleration with Chris Deotte and Jean-Francois Puget appeared first on Software Engineering Daily.

Today's guests are Ali Sarilgan, CEO & Ozge Islegen-Wojdyla, CTO at EcoTrove. Founded in 2023, EcoTrove's mission is to use technology to build a cheaper, greener and predictable energy ecosystem. They register as your automated energy agent to replace your utility bills with lower-cost, greener, fixed-price payment plans. Backed by leading Silicon Valley investors, EcoTrove are saving each customer an average of 7% off their power bills and 32% off their carbon emissions. CEO and Co-Founder Ali previously led corporate strategy for consumer technology companies and clean technology providers, and advised energy utilities. He also graduated with MS and BS from Stanford. CTO and Co-Founder Ozge is a former Assistant Professor at Northwestern and Stanford PhD focused on energy markets. She previously led statistical interventions and testing as Senior Data Scientist at Instacart. In this episode, Ali and Ozge talks about: Their career journey and passion to create AI for cleaner energy, Their AI-driven energy agent offering cheaper, greener utility solutions, How AI forecasts energy needs and optimizes usage for savings, Becoming an AI-powered energy advisor by optimizing utility relationships and efficiency, Expanding the team to enhance platform and marketing efforts, Seeking passionate candidates for greener energy solutions, Prioritizing carbon reduction, expanding markets and growing their team

Nicolas Augusti est Senior Data Scientist chez Qonto, la banque en ligne des PME et des indépendants, et également l'une des plus belles licornes françaises. La spécificité de l'équipe Data Science chez Qonto, c'est qu'elle fait de la data science appliquée à la décision.On aborde :

Today's guest is Deepak John Reji, Senior Data Scientist, and associated with University of Limerick. Discussing Deepak's AI Awards 2024 nomination in the Best Use of Responsible AI an Ethics category, this episode centres around the challenges and opportunities in creating safe and responsible large language models (LLMs) that strive to reduce bias and bolster ethical AI practices. Topics include: 0:00 Mitigating bias in AI through fine-tuned LLMs 5:23 Challenges in curating unbiased data and training models 8:39 How bias perception varies by context, demographics and culture 11:29 How diverse annotators ensured culturally representative bias assessments 12:53 Enabling scalable, domain-specific LLM solutions through Instruction-led fine-tuning 15:21 Focus on responsible AI, integrating ethics and cognitive science

Photo: Privat. Was sind die wichtigsten use cases für KI in der Erstversicherung? Wie groß ist der KI business case? Woran scheitert die Einführung von KI? Wie helfen LLMs data scientists. Dr. Marc Piopiunik ist Senior Data Scientist im Chief Data Office bei der Allianz Versicherungs-AG.  

The IfG team presented new analysis on the likely impact of the budget on public services performance. They also discussed the key questions facing the government ahead of the spending review, including widespread poor performance and record backlogs, tight funding settlements, industrial disputes, crumbling buildings, recruitment and retention problems, and resilience for future crises. Stuart Hoddinott, Senior Researcher at the Institute for Government Philip Nye, Senior Data Scientist at the Institute for Government Cassia Rowland, Senior Researcher at the Institute for Government This session was chaired by Emma Norris, Deputy Director of the Institute for Government. This event was part of the IfG's public services conference, kindly supported by UCL.

Tobias Zwingmann is an ex-Senior Data Scientist-turned managing partner of RAPYD.AI - which is empowering companies from B2B SaaS startups  to leading financial institutions towards a unified AI strategy.  His data insights are shared in his books including “AI-Powered Business Intelligence” (O'Reilly 2022) and “Augmented Analytics” (Co-author, O‘Reilly 2024) as well as weekly newsletter “The Augmented Advantage” read by 4,500+ business leaders from brands like Amazon, Mercedes-Benz, Gucci, and Santander.  In this episode: My rise in data science Did the latest changes to Co-Pilot actually make it good? What finance can learn from other departments using AI Consolidating reports and augmenting processes using AI  Let's talk forecasting and analytics and regression analysis  Leveraging Excel and Power BI to enhance their data analysis capabilities Getting to “data progressive” and “data active” in your organization  Augmented Analytics Explained  Clean (but not tidy) data in finance Two ways to make data tidy in ChatGPT Connect with Tobias Zwingmann on LinkedIn https://www.linkedin.com/in/tobias-zwingmann

Data is the lifeblood of any business, but the value is when you can just owning the data doesn't mean you're making a difference. Instead, studios need to see it in context. Safia Dawood, Senior Data Scientist at Moloco, shows them how on this week's show alongside our hosts Peggy Anne Salz and Brian Baglow. Having worked at both startups and top tech companies like Ubisoft and Meta, Safia dives deep into the data to discover what truly drives mobile game growth. She reveals Moloco's recent research on market trends, what top games are doing differently, and how to turn poor engagement around to help marketers determine what truly drives their mobile growth and what they need to be doing now to change the game—literally and figuratively. CHAPTER TIMESTAMPS 00:00 - Intro 02:25 - Data doesn't always tell the truth 05:04 - Market trends 2022-2024 07:13 - Adjusting for a slowdown 10:07 - How marketers should be leveraging data  12:56 - What top-performing games are doing differently    18:10 - How to turn poor engagement around 21:00 - 22% higher transaction value 23:00 - Driving repeat purchases 25:35 - Why is remarketing a critical part of growth 27:22 - Engage to retain 33:30 - How top games invest differently  35:15 - Emerging trends and opportunities gaming companies should be paying attention to 36:42 - What's next for Safia 39:19 - Favourite games Q&A * * * * * * * * * * * * * * *  ** Let's Connect **

In this episode of the Crazy Wisdom podcast, Stewart Alsop speaks with Anand Dwivedi, a Senior Data Scientist at ICE, returning for his second appearance. The conversation covers a range of topics including the evolution of machine learning models, the integration of AI into operating systems, and how innovations like Neuralink may reshape our understanding of human-machine interaction. Anand also touches on the role of cultural feedback in shaping human learning, the implications of distributed systems in cybersecurity, and his current project—training a language model on the teachings of his spiritual guru. For more information, listeners can connect with Anand on LinkedIn.Check out this GPT we trained on the conversation!Timestamps00:00 Introduction and Guest Welcome00:25 Exploring GPT-4 and Machine Learning Innovations03:34 Apple's Integration of AI and Privacy Concerns06:07 Digital Footprints and the Evolution of Memory09:42 Neuralink and the Future of Human Augmentation14:20 Cybersecurity and Financial Crimes in the Digital Age20:53 The Role of LLMs and Human Feedback in AI Training29:50 Freezing Upper Layers and Formative Feedback30:32 Neuroplasticity in Sports and Growth32:00 Challenges of Learning New Skills as Adults32:44 Cultural Immersion and Cooking School34:21 Exploring Genetic Engineering and Neuroplasticity38:53 Neuralink and the Future of AI39:58 Physical vs. Digital World41:20 Existential Threats and Climate Risk45:15 Attention Mechanisms in LLMs48:22 Optimizing Positive Social Impact54:54 Training LLMs on Spiritual LecturesKey InsightsEvolution of Machine Learning Models: Anand Dwivedi highlights the advancement in machine learning, especially with GPT-4's ability to process multimodal inputs like text, images, and voice simultaneously. This contrasts with earlier models that handled each modality separately, signifying a shift towards more holistic AI systems that mirror human sensory processing.AI Integration in Operating Systems: The conversation delves into how AI, like Apple Intelligence, is being integrated directly into operating systems, enabling more intuitive interactions such as device management and on-device tasks. This advancement brings AI closer to daily use, ensuring privacy by processing data locally rather than relying on cloud-based systems.Neuralink and Transhumanism: Anand and Stewart discuss Neuralink's potential to bridge the gap between human and artificial intelligence. Neuralink's brain-computer interface could allow humans to enhance cognitive abilities and better compete in a future dominated by intelligent machines, raising questions about the ethics and risks of such direct brain-AI integration.Cultural Feedback and Learning: Anand emphasizes the role of cultural feedback in shaping human learning, likening it to how AI models are fine-tuned through feedback loops. He explains that different cultural environments provide varied feedback to individuals, influencing the way they process and adapt to information throughout their lives.Cybersecurity and Distributed Systems: The discussion highlights the dual-edged nature of distributed systems in cybersecurity. While these systems offer increased freedom and decentralization, they can also serve as breeding grounds for financial crimes and other malicious activities, pointing to the need for balanced approaches to internet freedom and security.Generative Biology and AI: A key insight from the episode is the potential of AI models, like those used for language processing, to revolutionize fields such as biology and chemistry. Anand mentions the idea of generative biology, where AI could eventually design new proteins or chemical compounds, leading to breakthroughs in drug discovery and personalized medicine.Positive Social Impact Through Technology: Anand introduces a thought-provoking idea about using AI and data analytics for social good. He suggests that technology can help bridge disparities in education and resources globally, with models being designed to measure and optimize for positive social impacts, rather than just profits or efficiency.

Keir Starmer has appointed more than 100 ministers to his government since Labour won the general election on 4 July. Some were ministers in the last Labour government; for many this was their first time in ministerial office. So, who makes up this latest generation of government ministers? And who held office before them? The Institute for Government's brand new Ministers Database holds information about all government ministers since 1979 – who served as a minister, in what role, and for how long. On Thursday 5 September the IfG launched the database for public use, so that everyone can benefit from this unrivalled source of information and use it in their work. So what can we learn from the IfG's Ministers Database? Which ministerial roles have seen the most churn? How has turnover among ministers changed over time, and what does it mean for government? And how can academics, journalists and others use the IfG Ministers Database in their work? To explore these questions and more, we were joined on this webinar by an expert panel, including: Dr Catherine Haddon, Programme Director at the Institute for Government Philip Nye, Senior Data Scientist at the Institute for Government Dr Jessica Smith, Lecturer in Politics with Quantitative Methods at the University of Edinburgh The event was chaired by Tim Durrant, Programme Director at the Institute for Government. Release date: 5 September 2024

Our special guest, astrophysicist Rachel Losacca, explains the intricacies of galaxies, modeling, and the computational methods that unveil their mysteries. She shares stories about how advanced computational resources enable scientists to decode galaxy interactions over millions of years with true-to-life accuracy. Sid and Andrew discuss transferable practices for building resilient modeling systems. Prologue: Why it's important to bring stats back [00:00:03]Announcement from the American Statistical Association (ASA): Data Science Statement Updated to Include “ and AI”  Today's guest: Rachel Losacco [00:02:10]Rachel is an astrophysicist who's worked with major galaxy formation simulations for many years. She hails from Leiden (Lie-den) University and the University of Florida. As a Senior Data Scientist, she works on modeling road safety.  Defining complex systems through astrophysics [00:02:52]Discussion about origins and adoption of complex systemsDifficulties with complex systems: Nonlinearity, chaos and randomness, collective dynamics and hierarchy, and emergence.Complexities of nonlinear systems [00:08:20]Linear models (Least Squares, GLMs, SVMs) can be incredibly powerful but they cannot model all possible functions (e.g. a decision boundary of concentric circles)Non-linearity and how it exists in the natural worldChaos and randomness [00:11:30]Enter references to Jurassic Park and The Butterfly Effect“In universe simulations, a change to a single parameter can govern if entire galaxy clusters will ever form” - RachelCollective dynamics and hierarchy [00:15:45]Interactions between agents don't occur globally and often is mediated through effects that only happen on specific sub-scalesAdaptation: components of systems breaking out of linear relationships between inputs and outputs to better serve the function of the greater system   Emergence and complexity [00:23:36]New properties arise from the system that cannot be explained by the base rules governing the systemExamples in astrophysics [00:24:34]These difficulties are parts of solving previously impossible problemsConsider this lecture from IIT Delhi on Complex Systems to get a sense of what is required to study and formalize a complex system and its collective dynamics (https://www.youtube.com/watch?v=yJ39ppgJlf0)Consciousness and reasoning from a new point of view [00:31:45]Non-linearity, hierarchy, feedback loops, and emergence may be ways to study consciousness. The brain is a complex system that a simple set of rules cannot fully define.See: Brain modeling from scratch of C. Elgans What did you think? Let us know.Do you have a question or a discussion topic for the AI Fundamentalists? Connect with them to comment on your favorite topics: LinkedIn - Episode summaries, shares of cited articles, and more. YouTube - Was it something that we said? Good. Share your favorite quotes. Visit our page - see past episodes and submit your feedback! It continues to inspire future episodes.

In July 2024, we witnessed one of the most significant internet disruptions in history when CrowdStrike released a faulty update to its security servers. This update impacted approximately 8.5 million systems, triggering outages across various sectors, including airlines, banks, stock markets, and even government emergency services. Even once activity was restored, threat actors sought to take advantage of the situation through phishing schemes and other cyberattacks.  Though caused by an internal error rather than malicious intent, incidents like CrowdStrike's outage underscore the growing importance of reliable security measures on technologies that impact daily life. On this month's podcast, we explore the ins and outs of cybersecurity, how cyberattacks occur, and what steps you can take to protect your data. Our guests: Milena Rodban, independent geopolitical risk consultant and former senior advisor at the National Risk Management Center at the Cybersecurity and Infrastructure Security Agency (CISA). Arun Seelagan, Senior Data Scientist at the Cybersecurity and Infrastructure Security Agency (CISA)

Duplicate reports are a big problem when it comes to signal detection, but with the help of machine learning and new ways of comparing reports, we may more effectively detect them. This episode is part of the Uppsala Reports Long Reads series – the most topical stories from UMC's pharmacovigilance news site, brought to you in audio format. Find the original article here.After the read, we speak to author Jim Barrett, Senior Data Scientist at UMC, to learn more about the duplicate detection algorithm and UMC's work to develop AI resources for pharmacovigilance.Tune in to find out:How the new algorithm handles duplicates in VigiBaseAbout different approaches for developing algorithmsWhy it can be challenging to evaluate the performance of an algorithmWant to know more?Listen to the Drug Safety Matters interview with Michael Glaser about his Uppsala Reports article “Ensuring trust in AI/ML when used in pharmacovigilance” and check out the episode's extensive list of links for more on AI in pharmacovigilance. Artificial intelligence in pharmacovigilance – value proposition and the need for critical appraisal, a presentation by Niklas Norén, Head of Research at UMC, given at University of Verona in April 2024.  Finally, don't forget to ­subscribe to the monthly Uppsala Reports newsletter for free regular updates from the world of pharmacovigilance.Join the conversation on social mediaFollow us on X, LinkedIn, or Facebook and share your thoughts about the show with the hashtag #DrugSafetyMatters.Got a story to share?We're always looking for new content and interesting people to interview. If you have a great idea for a show, get in touch!About UMCRead more about Uppsala Monitoring Centre and how we work to advance medicines safety.

In this DSS Podcast, Anna Anisin welcomes Serg Masís, Climate and Agronomic Data Scientist at Syngenta. Serg, an expert in machine learning interpretability and responsible AI, shares his diverse background and journey into data science. He discusses the challenges of building fair and reliable ML models, emphasizing the importance of interpretability and trust in AI. Serg also talks into his latest book, "Interpretable Machine Learning with Python," and provides valuable insights for data scientists striving to create more transparent and effective AI solutions. In another compelling episode, Anna sits down with Nirmal Budhathoki, Senior Data Scientist at Microsoft. Nirmal, who has extensive experience at VMware Carbon Black and Wells Fargo, focuses on the intersection of AI and cybersecurity. He shares his journey into security data science, discussing the unique challenges and critical importance of applying AI to enhance cybersecurity measures. Nirmal highlights the pressing need for AI in this field, practical use cases, and the complexities involved in integrating AI with security practices, offering a valuable perspective for professionals navigating this dynamic landscape.

Immigration is essential for a functioning food system that otherwise suffers from growing labor shortages on farms, packing houses, processors and kitchens. The H-2A Temporary Agriculture Worker Program allows U.S. employers that face a shortage of domestic workers to hire foreign nationals for temporary or seasonal agricultural jobs.  An American Immigration Council analysis, “The Expanding Role of H-2A Workers in U. S. Agriculture” reveals significant demand across the country with labor being sought from two thirds (2/3) of all counties in the U.S. Steve Hubbard, the Senior Data Scientist at the American Immigration says “Instead of vilifying migrant workers, we should champion and protect them for their vital support to America's food production. www.americanimmigrationcouncil.org

Liberty Vittert is a Professor of Data Science at Wash U, Feature Editor of the Harvard Data Science Review, and Senior Data Scientist at Decision Desk HQ. She joined us today to discuss the ever growing and changing world of artificial intelligence, and how other nations like China may use it to wreak havoc in the States.

In this episode, Dave and Jamison answer these questions: Hi :-) I work as a Senior Data Scientist, and about half a year ago I joined a start up that was founded by a large corporation. And while this job comes with the perks of a bigger company - like good salary, paid overtime, … , - it also comes with its organizational overhead and politics: We are only about 30 people but already a quarter of us acts as managers. I write “act” because the official org chart is flat (with the CEO at the top and the rest of us directly underneath). The unofficial org chart is hidden and depending on who you speak with, you get their view point on how roles and responsibilities should look like. As a result, I'm left with putting together the pieces to build a picture that somewhat resembles the truth. So far, I've concluded that we have multiple (!) management layers, that there's a power war taking place in the middle management layer, and that you can make up your own titles that mean NOTHING, because no one has any official, disciplinary authority over any one, but that are still to be respected! What a great opportunity for job crafting :-D To make things worse, I prefer and come from organizations that have a truly flat hierarchy. For example, I'm used to step outside of my role should the situation require it (like doing some managerial tasks, supporting sales, …) and that I can speak my mind, irrespective of what the title of the person is who I'm talking to. While this was beneficial in my previous positions, this does not work well here! And while I understand that adapting my behavior would be more in line with the company culture, I find this extremely difficult. On the one hand, because of the hidden org chart, on the other because we are all fully remote and I rarely see people from other teams. To avoid accidentally stepping on anyone's toes, my current solution is to stick my head in the sand and focus on my coding. However, this leaves me disgruntled because I feel like I'm not being myself, and that I'm withholding a viable part of my skill set: to see the bigger picture and serve the company as a whole instead of just implementing tickets. Please help, I do not understand how this company works :'-D How would you navigate the situation? I don't want to quit because, individually, my coworkers are super nice, and the work is really interesting. All the best

Today's guest is Valentino Constantinou, Senior Data Scientist, Team Lead at Terran Orbital. Founded in 2013, Terran Orbital is a leading manufacturer of satellite products primarily serving the aerospace and defense industries. The company provides end-to-end satellite solutions by combining satellite design, production, launch planning, mission operations and on-orbit support to meet the needs of the most demanding military, civil and commercial customers. Valentino is an experienced, creative problem solver and leader in analytics and AI for the aerospace industry, serving as a Senior Data Scientist and Team Lead at Terran Orbital since April 2023. He previously at the NASA Jet Propulsion Laboratory where he served as the Principal Investigator to a multi-year alarm analytics effort and contributed to innovative research and technology development efforts. His efforts at the Laboratory have resulted in numerous technology releases, publications and patents, including the open-source PyNomaly software. In today's episode, Valentino talks about: His background and journey to Terran Orbital, How Terran Orbital streamlines satellite manufacturing with AI, An insight into the day-to-day life of the team, Enhancing internal processes for cost-efficient satellite manufacturing, Terran Orbital's diverse impact to accelerate industry innovation

Today I had the pleasure of interviewing Mark Moyou. Mark is a Senior Data Scientist at NVIDIA and the host of the AI portfolio podcast and the Caribbean Tech Pioneers podcast. He grew up in Trinidad and Tobago and his work is deeply inspired by his family and upbringing there. In this episode, we dive into how he landed his first job in the states, what makes a successful data scientist, how to make meaningful connections, and how work at NVIDIA is different than his previous jobs. Podcast Sponsors, Affiliates, and Partners:- Pathrise - http://pathrise.com/KenJee | Career mentorship for job applicants (Free till you land a job)- Taro - http://jointaro.com/r/kenj308 (20% discount) | Career mentorship if you already have a job - 365 Data Science (57% discount) - https://365datascience.pxf.io/P0jbBY | Learn data science today- Interview Query (10% discount) - https://www.interviewquery.com/?ref=kenjee |  Interview prep questionsMark's Links:LinkedIn - https://www.linkedin.com/in/markmoyou/

How can technology amplify human capabilities? Today, we're diving into the world of Human-Computer Interaction to explore the cutting-edge field of Brain-Computer Interfaces. We're joined by Jaime Salas, a researcher and educator whose work at the Institution University of Envigado (IUE) in Colombia from 2021 to 2023 has impacted our understanding of these technologies. At IUE, Jaime led initiatives in Industrial Automation and explored the field of Human-Computer Interaction, particularly through his work with Brain-Computer Interfaces. His approach integrates deep learning, signal processing, and experimental psychology, enhancing our interaction with machines. During his tenure, Jaime's research incorporated methods like electroencephalography and eye-tracking, to elevate user experience and system functionality. He also served as a Senior Data Scientist, developing key metrics for Digital Transformation and assessing technological impacts on society. Before starting his current PhD studies at Potsdam University, where he focuses on multimodal interactions between humans and robots, Jaime's contributions laid foundational work in digital innovation. Join us as we explore Jaime Salas's contributions to Human-Computer Interaction before he transitioned to his current research endeavors! About the Podcast Guest: Jaime's academic journey is rich and diverse. After earning his Master's degree in Computer Science from UFRGS in Porto Alegre, Brazil, he returned to his roots in Colombia where he served as a mechatronics engineer, educated at ITM in Medellin. His extensive teaching experience includes roles as an Assistant Professor leading the Industrial Automation research line at the University of Envigado and as a lecturer at EAFIT in Medellin. Beyond academia, Jaime made significant contributions to the technology sector as a Senior Data Scientist at MINTIC in Bogotà, Colombia. There, he spearheaded projects on Digital Transformation and developed the Digital Gap Indexes, evaluating the technological impact on society. He has also held professorships at Mariana University and AUNAR in Pasto, Colombia. Jaime's expertise spans several cutting-edge areas, including Human-Computer Interaction (focusing on Brain-Computer Interfaces), Artificial Intelligence (specializing in Deep Learning), Robotics, and Signal Processing. His work in experimental psychology, utilizing tools like electroencephalography and eye tracking, further underscores his commitment to understanding the nuances of human interaction with digital interfaces. Connect with Jaime Salas on LinkedIn: https://www.linkedin.com/in/jars0829/ About the Podcast Host: The Neurocareers podcast is brought to you by The Institute of Neuroapproaches (https://www.neuroapproaches.org/) and its founder, Milena Korostenskaja, Ph.D. (Dr. K), a neuroscience educator, research consultant, and career coach for people in neuroscience and neurotechnologies. As a professional coach with a background in the field, Dr. K understands the unique challenges and opportunities job applicants face in this field and can provide personalized coaching and support to help you succeed. Here's what you'll get with one-on-one coaching sessions from Dr. K: Identification and pursuit of career goals Guidance on job search strategies, resume, and cover letter development Neurotech / neuroscience job interview preparation and practice Networking strategies to connect with professionals in the field of neuroscience and neurotechnologies Ongoing support and guidance to help you stay on track and achieve your goals You can always schedule a free neurocareer consultation/coaching session with Dr. K at https://neuroapproaches.as.me/free-neurocareer-consultation Subscribe to our Nerocareers Newsletter to stay on top of all our cool neurocareers news at updates https://www.neuroapproaches.org/neurocareers-news 

No matter what industry you work in, data is all around you. Understanding and harnessing that data is essential to unlocking your organization's full potential.This week, Ranjeeta Bhattacharya, Senior Data Scientist at BNY Mellon's AI Hub, joins Joe to discuss data science, its many applications, and the most important skills for success in the field. Ranjeeta's current focus is on data science's role in the financial sector, and she brings plenty of sharp insights into the importance of diverse backgrounds and skill sets for data scientists — as well as the challenges of applying innovations within the field (like AI) to all manner of industries.Join us as we discuss:The role of communication, metrics, and analytics in getting the most out of your dataAddressing skeptics who aren't sold on AIHow AI can help with issues ranging from customer attrition and fraud protection

In this episode Evan Wimpey sits down to chat with Nirmal Budhathoki. A seasoned data scientist at Microsoft, Nirmal has extensive experience in both cybersecurity and the tech industry. During the conversation Nirmal discusses his unique career journey, from unexpected detours, including serving in the Army, to becoming a data scientist. He also talks about applications of machine learning in cloud security, emphasizing the need for proactive defense strategies. Additionally, Nirmal offers advice for aspiring data scientists and highlights the ongoing advancements in the field. In this episode you will learn: ⛛ How individuals from diverse experiences can excel in data science⛛ The importance of proactive defense strategies in cybersecurity⛛ The need for community engagement and mentorship in the field of data science⛛ How Large Language Models (LLMs) can be used to enhance cybersecurity measuresQuote

Featuring Danny Kim, Senior Data Scientist at Sony Pictures. (Recorded 1/19/24)

Axon's Moonshot initiative has an ambitious goal to drastically reduce gun-related deaths in encounters involving police officers and the public. The primary aim of the Moonshot initiative is to reduce these fatalities by 50% within 10 years. In this episode of the "Policing Matters" podcast, host Jim Dudley engages with Axon's experts to unravel the complexities of officer-involved shootings and the potential for reducing gun fatalities. Axon has initiated an ambitious project: the Axon Public Safety Gun Fatality Database. This database, a product of meticulous research and analysis in collaboration with the Institute for Intergovernmental Research (IIR), aims to provide groundbreaking insights into shooting deaths involving officers and civilians from 2021 through June 2023 across all U.S. jurisdictions. The discussion pivots on the genesis and objectives of Axon's Moonshot goal and the database. Guests Mike Wagers, Senior Vice President of Strategic Initiatives at Axon, and Ty Nguyen, Senior Data Scientist, discuss the unique approach and methodology behind the database, highlighting how it stands apart from existing studies. The episode also explores the initial findings and their implications for enhancing law enforcement training, decision-making and safety. About our sponsor This episode of the Policing Matters Podcast is brought to you by Lexipol, the experts in policy, training, wellness support and grants assistance for first responders and government leaders. To learn more, visit lexipol.com.

Гостем сегодняшнего выпуска стал Юрий Окуловский - Senior Data Scientist, кандидат физико-математических наук, ранее руководитель лаборатории искусственного интеллекта и робототехники УрФУ, также вы, возможно, его знаете как автора нескольких видеокурсов по программированию и рациональному мышлению. Юрий уже был гостем подкаста примерно три года назад и мы снова решили встретиться пообщаться, тем более у Юрия интересный взгляд на происходящие изменения в обществе, связанные со стремительным развитием технологий. В подкасте обсуждаем как превратить нейросеть в своего личного литературного негра, нужно ли гуманоидное тело современному секс-роботу, как сделать свою собственную Алису из Бесконечного лета, почему менеджеров автоматизировать проще, чем программистов, почему дохли куры у Ленина, почему корпорации не могут позволить себе делать, действительно, персонализированные и полезные продукты на базе ИИ, а также многое-многое другое.Ссылки выпуска:Предыдущий выпуск подкаста с Юрием "Искусственный Интеллект в мире моды и как подготовиться к Сингулярности" (https://mlpodcast.mave.digital/ep-11)Курсы по программированию (Юрия и не только): https://ulearn.meКурс Юрия по Научному Мышлению: https://stepik.org/course/578Телеграмм-канал Свидетели сингулярности: https://t.me/witnessesofsingularityСсылки на технологии, обсуждаемые в подкасте (https://t.me/toBeAnMLspecialist/786)Буду благодарен за обратную связь!Вступайте в книжный ML-клуб, где мы читаем книги по машинному обучению и смежным темам!MLBookClub (https://t.me/+HIXnIwXIIFAyYzYy). Условия участия (https://t.me/toBeAnMLspecialist/750)Подписывайтесь на телеграм-канал "Стать специалистом по машинному обучению" (https://t.me/toBeAnMLspecialist)Мой телеграм для связи (https://t.me/kmsint)Также со мной можно связаться по электронной почте: kms101@yandex.ruЯ сделал бесплатный курс по созданию телеграм-ботов на Python и aiogram на Степике (https://stepik.org/120924). Присоединяйтесь, если хотите научиться разрабатывать телеграм-ботов!И буквально месяц назад я открыл доступ к пре-релизу нового курса по продвинутой разработке телеграм-ботов с элементами микросервисной архитектуры (https://stepik.org/a/153850?utm_source=mlpodcast&utm_campaign=ep_56)Выразить благодарность можно добрым словом и/или донатом (https://www.tinkoff.ru/rm/kryzhanovskiy.mikhail11/NkwE718878/)

It's that time of year once again … LegalWeek!    ALM's LegalWeek is one week where thousands of legal professionals gather to network with their peers, dive deeper into their professional development, explore topics and strategies tailored specifically to their role, and gain the tools to get legal business done.  The LegalSpeak show has now become a regular staple at the conference as we talk to some of the leading legal minds across the industry.  In this episode, Zack and Alaina give a preview of the Day 1 AI Workshop panel ... as they sit down with Danielle Beneke the Founder & Director of Baker McKenzie Machine Learning, Leo Murgel, SVP & COO, Legal and Corporate Affairs at Salesforce and Zonghui Wei, Senior Data Scientist at Baker McKenzie Machine Learning Practice.

MLOps Coffee Sessions Special episode with Weights & Biases, Model Management in a Regulated Environment, fueled by our Premium Brand Partner, Weights & Biases. // Abstract Step into the fascinating world of Language Model Management (LLMs) in a Regulated Environment! Join us for an enlightening chat where we'll explore the intricacies of managing models within highly regulated settings, focusing on compliance and effective strategies. This is your opportunity to be part of a dynamic conversation that delves into the challenges and best practices of Model Management in Regulated Environments. Secure your spot today and stay tuned for an enriching dialogue on navigating the complexities of navigating the regulated terrain. Don't miss out on the chance to broaden your understanding and connect with peers in the field! // Bio Darek Kłeczek Darek Kłeczek is a Machine Learning Engineer at Weights & Biases, where he leads the W&B education program. Previously, he applied machine learning across supply chain, manufacturing, legal, and commercial use cases. He also worked on operationalizing machine learning at P&G. Darek contributed the first Polish versions of BERT and GPT language models and is a Kaggle Competitions Grandmaster. Mark Huang Mark is a co-founder and Chief Architect at Gradient, a platform that helps companies build custom AI applications by making it extremely easy to fine-tune foundational models and deploy them into production. Previously, he was a tech lead in machine learning teams at Splunk and Box, developing and deploying production systems for streaming analytics, personalization, and forecasting. Prior to his career in software development, he was an algorithmic trader at quantitative hedge funds where he also harnessed large-scale data to generate trading signals for billion-dollar asset portfolios. Oliver Chipperfield Oliver Chipperfield is a Senior Data Scientist and Team Lead at M-KOPA, where he utilizes his expertise in machine learning and data-driven innovation. At M-KOPA since October 2021, Oliver leads a diverse tech team, making improvements in credit loss forecasting and fraud detection. His career spans multiple industries, where he has applied his extensive knowledge in Python, Spark, R, SQL, and Excel. He also specialized in the building and design of production ML systems, experimentation, and Bayesian statistics. Michelle Marie Conway As an Irish woman who relocated to London after completing her university studies in Dublin, Michelle spent the past 12 years carving out a career in the data and tech industry. With a keen eye for detail and a passion for innovation, She has consistently leveraged my expertise to drive growth and deliver results for the companies she worked for. As a dynamic and driven professional, Michelle is always looking for new challenges and opportunities to learn and grow, and she's excited to see what the future holds in this exciting and ever-evolving industry. // MLOps Jobs board https://mlops.pallet.xyz/jobs // MLOps Swag/Merch https://mlops-community.myshopify.com/ // Related Links Fine-Tuning LLMs: Best Practices and When to Go Small // Mark Kim-Huang // MLOps Meetup #124 - https://youtu.be/1WSUfWojoe0 --------------- ✌️Connect With Us ✌️ ------------- Join our slack community: https://go.mlops.community/slack Follow us on Twitter: @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Catch all episodes, blogs, newsletters, and more: https://mlops.community/ Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Darek on LinkedIn: https://www.linkedin.com/in/kleczek/ Connect with Mark on LinkedIn: https://www.linkedin.com/in/markhng525/ Connect with Oliver on LinkedIn: https://www.linkedin.com/in/oliver-chipperfield/ Connect with Michelle on LinkedIn: https://www.linkedin.com/in/michelle-conway-40337432

In this episode we'll talk with Sean Gilligan, chief operating officer at AVS (Amplitude Vascular Systems), about that company's big play in intravascular lithotripsy, the approached pioneered by vascular leader Shockwave Medical. Gilligan gives some detail on the company's new approach and shares some insights from his own career as well. We also visit with Steve Levine, Sr. Director, Virtual Human Modeling, and Afrah Shafquat, Senior Data Scientist, both of Dassault Systemes, which sponsored this episode. The pair shared insights on what medical device companies can expect to see from a new set of guidelines being issued for digital simulations in Medtech regarding in silico clinical trials. For more information go to https://www.3ds.com/industries/life-sciences-healthcare/medical-device. Thanks for listening to the DeviceTalks Weekly Podcast. Subscribe to the DeviceTalks Podcast Network so you don't miss an episode.

Recorded on Aug 25, 2023 in Berlin, Germany.   Video version available on YouTube Is Marketing Intrinsically Causal? After spending 5 years talking to mathematicians, Juan decided to look for new opportunities that would offer him more immediate impact on the world. Little did he know that this journey will lead him to become a Senior Data Scientist at Wolt - one of the global food delivery leaders with operations in 25 countries. In this episode we discuss Juan's journey towards data science, how causality was close to his heart from the very beginning and why starting simple is a good thing. Juan shares how his background in physics and advanced geometry helps him tackle causal problems he faces daily in his work in the fields of marketing and pricing. "It's fundamental for decision-making" - he says when asked about the future of causal modeling and causal AI. We discuss the consequences of ignoring the causal structure in marketing problems. Finally, Juan shares how inaccurate world models contributed to a distaste for wearing gloves by someone dear to him. Ready to dive in? About The Guest Juan Orduz, Phd is a Senior Data Scientist at Wolt. He is a blogger and an open source contributor. Juan holds a PhD in geometric analysis. Connect with Juan: - Juan on LinkedIn - Juan on Twitter/X - Juan's Blog  About The Host Aleksander (Alex) Molak is an independent machine learning researcher, educator, entrepreneur and a best-selling author in the area of causality. Connect with Alex: - Alex on the Internet Links (see here for the full list) Causal Bandits Team Project Coordinator: Taiba Malik Video Editors: Navneet S., Aleksander Molak Causal Bandits PodcastCausal AI || Causal Machine Learning || Causal Inference & DiscoveryWeb: https://causalbanditspodcast.comConnect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/Join Causal Python Weekly: https://causalpython.io The Causal Book: https://amzn.to/3QhsRz4

In today's episode, we are joined by Dalia Shanshal, Senior Data Scientist at Bell, Canada's largest communications company that offers advanced broadband wireless, Internet, TV, media, and business communications services. With over five years of experience working on hands-on projects, Dalia has a diverse background in data science and AI. We start our conversation by talking about the recent GeekFest Conference, what it is about, and key takeaways from the event. We then delve into her professional career journey and how a fascinating article inspired her to become a data scientist. During our conversation, Dalia reflects on the evolving nature of data science, discussing the skills and qualities that are now more crucial than ever for excelling in the field. We also explore why creativity is essential for problem-solving, the value of starting simple, and how to stand out as a data scientist before she explains her unique root cause analysis framework.Key Points From This Episode:Highlights of the recent Bell GeekFest Conference.AI-related topics focused on at the event.Why Bell's GeekFest is only an internal conference.Details about Bell and Dalia's role at the company.Her background and professional career journey.How the role of a data scientist has changed over time.The importance of creativity in problem-solving.Overview of why quality data is fundamental.Qualities of a good data scientist.The research side of data science.Dalia reveals her root cause analysis framework.Exciting projects she is currently working on.Tweetables:“What I do is to try leverage AI and machine learning to speed up and fastrack investigative processes.” — Dalia Shanshal [0:06:52]“Data scientists today are key in business decisions. We always need business decisions based on facts and data, so the ability to mine that data is super important.” — Dalia Shanshal [0:08:35]“The most important skill set [of a data scientist] is to be able to [develop] creative approaches to problem-solving. That is why we are called scientists.” — Dalia Shanshal [0:11:24]“I think it is very important for data scientists to keep up to date with the science. Whenever I am [faced] with a problem, I start by researching what is out there.” — Dalia Shanshal [0:22:18]“One of the things that is really important to me is making sure that whatever [data scientists] are doing has an impact.” — Dalia Shanshal [0:33:50]Links Mentioned in Today's Episode:Dalia ShanshalDalia Shanshal on LinkedInDalia Shanshal on GitHubDalia Shanshal EmailBellGeekFest 2023 | BellCanadian Conference on Artificial Intelligence (CANAI)‘Towards an Automated Framework of Root Cause Analysis in the Canadian Telecom Industry'Ohm Dome ProjectHow AI HappensSama

“When you stop seeing numbers, and you start seeing people in your data sheets, everything changes.” - Favio Vazquez   In this episode, our host, Chris Richardson, interviews Favio Vazquez, Senior Data Scientist at H20.ai.   This conversation dives deep into all things autoML and AI, from what companies are doing now to what data professionals can do to prepare for the future. Favio provides his strategies for screening for bias and competing in a job market where AI is changing how we work.   They discuss: What to expect in the transition from data science in academia to data science in business What it means to practice data science in an Agile environment Why AI and autoML won't replace data professionals any time soon How to approach ethics in machine learning New roles for data professionals Business-Driven Data Analysis As discussed in this podcast, transitioning to a business environment requires a different lens to interpret and analyze data.   A business-driven approach to data analysis enhances decision-making and aligns data projects with organizational objectives.   Our course, Business-Driven Data Analysis, will train you to learn what a stakeholder truly wants, refine the project based on available data, produce results and provide strategic insights.   Learn More

John Tyminski, OCEARCH's Senior Data Scientist, spoke to Newsline with Brigitte Quinn about great whites Simon and Jekyyl, who have swam from Georgia to Northern Canada in synchronicity.

In this episode we spoke with Gabriel Golczer-Gatti, PhD about his experience going to graduate school at Tufts University, choosing a career in industry instead of academia, the day to day of a data scientist on a biotech startup and his volunteer work for the Universidad Simon Bolivar Alumni Association of America Inc.## SHOW NOTESFor feedback or business inquiries reach out to hello @ latinoswhotech.comIf you enjoy this content and want to support, you can buy me a coffee: https://www.buymeacoffee.com/hugocastellanosFor Feedback or Questions, you can reach out to me via LinkedIn. I read every message. https://www.linkedin.com/in/hugocastellanosSign up for our mailing list: https://lwt-email.ck.page/d3749616a6Connect with Dr. Golczer-Gatti: https://www.linkedin.com/in/ggolczer/Support AlumnUSB's cause: https://alumnusb.org/es/becas/

There will be more than 13,000 job openings annually across the U.S. for data scientists until 2031 – that's according to the US Bureau of Labor Statistics who also shares the median wages for those jobs will be more than 100,000 dollars. These numbers are big and they are across agbioscience. Dr. Sofia Brandariz Zerboni, Senior Data Scientist with Bayer, joins us to share her perspective on the opportunity and new partnerships making data science more accessible to companies and students across the Midwest.  Sofia talks about data science informing better decision making, Bayer's approach to innovation and the average day of a data scientist in agbioscience. She gets into the company's partnership with The Data Mine at Purdue University and enabling students from various backgrounds to understand the application of data science in the agbioscience. Diving into data making a better world, Sofia shares her advice for young people considering their career and agbioscience being a good fit for them. 

Join us for an enlightening episode as we sit down with AI expert Dr. Bobby Rohrkemper, Senior Data Scientist in Fraud and Risk Management & AI Champion, to explore the transformative impact of AI on electronic banking. With expertise in AI, Dr. Rohrkemper reveals how AI-powered algorithms streamline banking operations, enhance fraud detection, and improve customer experiences. Don't miss this captivating conversation on the cutting-edge AI advancements reshaping the future of electronic banking! Want to learn even more? https://worldline.com/en/home/main-navigation/solutions/financial-institutions/authentication-and-security/fraud-management.html https://open.spotify.com/show/6Q7yo1f2EpxYalpyJTNssz https://podcasts.apple.com/gb/podcast/navigating-digital-payments/id1605184060 https://worldline.com/en/home/main-navigation/resources/themes/Innovation.html

The era of generative AI needs humans… not just the data sets they create. Now and going forward, companies will need to depend on perceptive, intelligent, creative humans who can evaluate and, when necessary, stand up to the black box output AI throws at them. What kind of traits do such people embody? Where might we find them? What might they teach the rest of us? That's what this episode of *Silo Busting* is all about. Tariq King, VP and Head of Product-Service Systems, and Ira Livshits, Senior Data Scientist at EPAM, meet the test-based questions of Producer Ken Gordon with knowledge and aplomb. King, who spent much of his career hiring testers, says he looks for “the way that someone actually approaches solving problems and thinking perhaps in a different way or from a different perspective.” Livshits notes that with testing in generative AI, “sometimes there is no right or wrong” and that a tester will “have to act or decide based on his or her understanding of the field and maybe intuition.” In short, she says, testing has become much less of a black-and-white job. Together King and Livshits create a model conversation. They talk about how explainability fits in here, why musicians and liberal arts people make for good testers, the importance of being able to relate findings to a given audience (“[if] I have a PhD focused on machine learning, probably I can understand certain things in a different way than someone who may not have that degree,” says King), and how generative AI is bringing the role of testing closer to the fore. Go on, give it a test-listen. Host: Alison Kotin Engineer: Kyp Pilalas Producer: Ken Gordon

We launched a swim collection!! Holy cow!! Kelly & I are back again for year two of our swim collection #doboth & are SO excited to share our journey. We are just two women with full time careers, a passion for fashion, & desire to show the world how you can balance both. I'm this episode, Kelly & I dive into how we connected, our first idea to launch a swim line together, how we came up with colors, cut, and more! We share why we think it's empowering to not just model but design swimwear and how it's impacted our mission to uplift women. Tune in to hear how this project became a reality! Kelly Cahill is a Pittsburgh-based entrepreneur and fashion enthusiast. She is the owner & founder of Swim by KC. In addition to her entrepreneurial pursuits, Kelly also works full time at Ralph Lauren as a Senior Data Scientist, where she uses her background in mathematics, and her love of fashion, to drive e-commerce business. Kelly lives the #DOBOTH message every day, and is so excited to collab with Kellie on their second swim launch together! Check out www.swimbykc.com or @swimbykc to check out the #doboth swim collection! Use code DOBOTH for 15% off your purchase! _________________________________ Follow https://www.instagram.com/missunderstood.podcast/ + https://www.instagram.com/kellie.sbrocchi/ on Instagram for episode updates + more. Special thank you to USEHATCH.FM for producing this episode.  The views and opinions presented herein are those of the author and do not necessarily represent the views of DoD or its Components. Appearance of, or reference to, any commercial products or services does not constitute DoD endorsement of those products or services. The appearance of external hyperlinks does not constitute DoD endorsement of the linked websites, or the information, products or services therein. --- Send in a voice message: https://podcasters.spotify.com/pod/show/missunderstoodkellie/message

MLOps Coffee Sessions #153 with Rodolfo Núñez, Multilingual Programming and a Project Structure to Enable It, co-hosted by Abi Aryan. // Abstract It's really easy to mix different programming languages inside the same project and use a project template that enables easy collaboration. It's not about what language is better, but rather what language solves the given section of your problem better for you. // Bio Rodo has been working in the "Data Space" for almost 7 years. He was a Senior Data Scientist at Entel (a Chilean telecommunications company) and is now a Senior Machine Learning Engineer at the same company, where I also lead three mini teams dedicated to internal cybersecurity; design/promote continuous training for the entire Analytics team and also the whole company; and ensure the improvement of programming practices and code cleanliness standards. Rodo is currently in charge of helping the team put models into production and define the tools that we will use for it. He specializes in R, but he's language/tool agnostic: you should use the tool that best solves your current problem. Rodo studied Mathematical Engineering and MSc in Applied Mathematics at the University of Chile in addition to General Engineering at the École Centrale Marseille. Rodo really likes to share knowledge (bi-directionally) in whatever he thinks he can contribute. Some things that Rodo like teaching are Data Science, Math, Latin Dances, and whatever he thinks he can give to people. Rodo's other interests are computer games (especially Vermintide and Darktide), board games, and dancing to Latin rhythms. Also, he streams some games and Data Science related topics on Twitch. // MLOps Jobs board https://mlops.pallet.xyz/jobs // MLOps Swag/Merch https://mlops-community.myshopify.com/ // Related Links https://www.twitch.tv/en_codershttps://www.youtube.com/@en_codershttps://www.twitch.tv/rodonunezhttps://github.com/rodo-nunezhttps://github.com/en-coders-cl --------------- ✌️Connect With Us ✌️ ------------- Join our slack community: https://go.mlops.community/slack Follow us on Twitter: @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Catch all episodes, blogs, newsletters, and more: https://mlops.community/ Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Abi on LinkedIn: https://www.linkedin.com/in/goabiaryan/ Connect with Rodo on LinkedIn: https://www.linkedin.com/in/rodonunez/ Timestamps: [00:00] Rodo's preferred coffee [00:16] Project structure [00:34] Introduction to Rodolfo Núñez [01:20] Takeaways [04:34] Check out our Meetups, podcasts, newsletters, TikTok, and blog posts! [05:50] Why data scientists should know how to code and code properly [10:32] Becoming a team player [14:02] Cookie cutter project [17:50] Markdown and Quarter over Jupyter notebooks [23:18] Data scientists' templates [30:06] Significance of scripts [33:30] Monolith to Microservices [34:33] Reproducibility [36:37] Entire event processing scripts [40:44] In-House cataloging solution [42:08] Data flows [46:00] Bonus topics! [47:23] Elbow methodology [50:17] Idea behind cross sampling [50:51] Machine Learning and MLOps Security at Entel [58:04] Wrap up

The Inflation Reduction Act allocates billions for home and building upgrades over the next ten years; these rebates and incentives can cut energy bills, reduce energy burdens, improve public health, and slash emissions, but state and tribal governments must work quickly to develop and implement well-designed programs to realize their full potential. This episode features energy policy researchers Dr. Yunus Kinkhabwala of PSE Healthy Energy and Dr. Arjun Makhijani of the Institute for Energy and Environmental Research, as well as heat pump and energy efficiency expert Dana Fischer with Mitsubishi Electric US discussing program design, data-driven approaches, and strategies that help people, especially low- to moderate income households and underserved communities, benefit from new funding. Guest BiosDr. Arjun Makhijani, PhD is the President of the Institute for Energy and Environmental Research holds a Ph.D. in engineering (specialization: nuclear fusion) from the University of California at Berkeley. He has produced many studies and articles on nuclear fuel cycle related issues. He is the principal author of the first study  on energy conservation potential in the U.S. economy. Most recently, Dr, Makhijani has authored Carbon-Free and Nuclear-Free: A Roadmap for U.S. Energy Policy (IEER Press), the first analysis of a transition to a U.S. economy based completely on renewable energy. He is the principal editor of Nuclear Wastelands and the principal author of Mending the Ozone Hole, both published by MIT Press.Dr. Yunus Kinkhabwala, PhD is a Senior Data Scientist, PSE Healthy Energy, where he develops sophisticated data-driven models to guide decision making and policy. Projects include optimizing the geospatial siting of solar and storage resilience hubs for vulnerable populations and estimating detailed household energy usages and costs to investigate impacts of policy scenarios aimed at improving energy affordability for low-income households. He received his PhD in Applied Physics from Cornell University as a National Science Foundation Graduate Research Fellow and holds a BS in Physics from the University of Illinois at Urbana-Champaign. Dana Fischer is the Director of Regulatory Strategy at Mitsubishi Electric US and has been with Mitsubishi Electric for 5 years working with individual homeowners and utility and industry organization and to the US Secretary of Energy. He was the Program Manager of the Home Energy Savings Program at Efficiency Maine and established the still active residential rebate and loan programs for weatherization, conventional heating systems, and heat pumps. He also has background in municipal finance, solar thermal, and ultra-high purity manufacturing.To dig in deeper, check out these must-read resources: Energy Affordability in Maryland: Integrating Public Health, Equity, and Climate | PSE Healthy Energy (February 2023)Mitsubishi Electric http://us.mitsubishielectric.comPSE Healthy Energy https://www.psehealthyenergy.orgInstitute for Energy and Environmental Research https://ieer.orgEfficiency Maine Heat Pump Program https://www.efficiencymaine.com/about-heat-pumps/

Today on the Data Futurology podcast, we have Ann Sebastian, Senior Data Scientist at Wesfarmers OneDigital, as a guest on the podcast. As Sebastian says, she is “in the trenches” building data science products. One of her key projects in recent years has been OnePass, a subscription service that provides free delivery and other services across a range of Australia's top brands. “It's an incredible experience to be part of a journey, developing an idea through to proof of concept through to production ideation to a system that is adopted across the organisation,” she said. Through the podcast, Sebastian offers some key insights into that process via some of the projects that she has worked on over the years. Sebastian also spoke about how data science teams can be built, and how a culture of innovation can be structured within them. For just one example of this that she shares on the podcast, in her current role there is a focus on learning and development, which manifests as 10 per cent of each person's work time being dedicated to research activities. For her part, Sebastian is currently using that research time to work on multimodal product classification, she said. “Given the fast-moving nature of retail catalogue, and need for us as a division to form a unified view across all our divisions products, there is business significance for this research project. “We then have fortnightly quick check ins to discuss the progress on our research projects, and that really helps us to learn from each other. This is one way that data science is embedded into our day to day in a way that makes it more real for us.” For these insights and more on how data science products are built and evaluated, and how data scientists can be motivated and innovative within their careers, tune in to the full podcast. Enjoy the show! Click here to learn more about OnePass Thank you to our sponsor, Talent Insights Group! Join us in Sydney for Ops World: https://www.datafuturology.com/opsworld Join our Slack Community: https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng What we discussed: 0:00 Introduction 3:00 Ann talks about her experience and her remit at Wesfarmers 7:44 What are some of the use cases you're proudest of? 15:12 Ann shares more information about her favourite use case and how it evolved from an idea to the start of the technical work. 17:58 How did you measure business impact? 20:14 How did you operationalize the models? 24:00 Can you describe your current role? 31:23 What's your advice for people wanting to get into data science? Quotes: · Business teams can sometimes view data science as a mythical creature, so I love working with them to demystify data science and achieve business benefits through it. · The use case that I'm proudest of is the automation of the complaint classification, where we implemented various natural language processing models to predict the category of the complaints using real time models. --- Send in a voice message: https://anchor.fm/datafuturology/message

Which states are the bellwethers in the upcoming election? Which states will give the clearest indication of the direction of the House and Senate? Who is showing up to vote that pollsters weren't expecting? And how will those voters who aren't considered "likely voters" change the results? How does a firm like Decision Desk HQ gather the information needed to make election calls as quickly as they do? (Answer: There are 50 states with 50 different ways to get the information.) What is a model? How are election models different from polls? What factors are considered to develop a model? What are some of the differences between DDHQ's model and other models such as fivethirtyeight's? How should we look at projections? We explore these questions and more with DDHQ's Senior Data Scientist Kiel Williams. Kiel Williams is a Senior Data Scientist at Decision Desk HQ. Decision Desk HQ collects, organizes, and reports election night results and provides election related data to media outlets, political organizations, and anyone interested in who votes and how they voted. Kiel specifically performs electoral analysis, polling and manages data operations at DDHQ. Kyle has an undergraduate degree in physics and math from Guilford College and earned his PhD in physics from the University of Illinois, Urbana Champaign. decisiondeskhq.com/ twitter.com/DecisionDeskHQ twitter.com/KielTWilliams twitter.com/coreysnathan

On today's episode, we dive into the world of operations through the lens of data science with Marc Jansen, Senior Data Scientist at Amazon. Marc's journey is rich with stories of his time spent in supply chain operations and he generously shares the lessons he's gathered by applying data science within businesses. There's a ton I learned from Marc, but one of my favorites was this key piece of life advice for all of us— "Find something that energizes you. Find something that you bring to the table. And marry the two up the best you can." I think I'll go do just that.You can find Marc Jansen on LinkedIn.Learn more about my work at arianacofone.com or drop me a line at hello@arianacofone.com!From our sponsor: Unlock your creativity with Baronfig! Use code SECRET20 for 20% off your entire order. Minimum purchase of $50.00 required. Open to all customers with no usage limits. This exclusive offer is active today.https://secret-ops.captivate.fm/baronfig

Mark Freeman, Senior Data Scientist at Humu, joins Jon Krohn to talk about all things data engineering and offers listeners some critical tips for their data science career journey – from what it takes to get promoted to his number one tip for getting hired at a fast-growing capital-backed startup. In this episode you will learn: • How Humu leverages data and machine learning to improve workplace behaviors [10:38] • What is data engineering? [14:21] • What it takes to get promoted into more senior data science roles [20:55] • The differences between junior, senior, and staff data scientists [30:21] • Mark's top tools for data extraction, modeling, and pipeline engineering [37:08] • Mark's number one tip for getting hired at a fast-growing venture capital-backed startup [53:10] • Why all data scientists should be interested in Web3 [1:11:53] Additional materials: www.superdatascience.com/587