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Broadly writ, we're all in the business of data work in some form, right? It's almost like we're all swimming around in a big data lake, and our peers are swimming around it, too, and so are our business partners. There might be some HiPPOs and some SLOTHs splashing around in the shallow end, and the contours of the lake keep changing. Is lifeguarding…or writing SQL…or prompt engineering to get AI to write SQL…or identifying business problems a job or a skill? Does it matter? Aren't we all just trying to get to the Insights Water Slide? Katie Bauer, Head of Data at Gloss Genius and thought-provoker at Wrong But Useful, joined Michael, Julie, and Val for a much less metaphorically tortured exploration of the ever-shifting landscape in which the modern data professional operates. Or swims. Or sinks? For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
Highlights from this week's conversation include:The evolution of the data scientist role (1:03)Common problems in different companies (2:05)Measuring and curating content on Reddit (4:29)The challenges of working with unstructured content at Reddit and Twitter (11:03)Lessons learned from Reddit and applying them at Twitter (13:17)Data challenges and customer behavior analysis at GlossGenius (20:16)How the data scientist's role has changed over time (00:25:10)The essence of the data scientist/engineer role (29:00)Dynamics and overlaps between different data roles (32:09)The perfect data team for Twitter (34:19)Building a data team at a startup like GlossGenius (36:36)The right time to bring in a dedicated data person in a startup (38:52)The analytics engineer role (46:25)Challenges in implementing telemetry (50:31)Final thoughts and takeaways (52:24)The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we'll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.
In this bonus episode, Eric and Kostas preview their upcoming conversation with Katie Bauer of GlossGenius.
You've got some solid experience under your belt, and you're starting to feel like you're ready to move into a data leadership role. What does that even mean? Shifting your keystrokes from SQL to slide decks? Maybe (but maybe not). Katie Bauer, Head of Data at GlossGenius, has held multiple data leadership roles over the course of her career, and she penned a thoughtful post on the various tactics she employed to find a role that is a good fit. She wrote the post so that she wouldn't have to keep repeating herself when data folks in her network reached out for advice. But that didn't stop this podcast from reaching out to record a lively discussion on the topic! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
We talked about: Katie's background What is a data scientist? What is a data science manager? Quality of the craft How data leaders promote career growth Supporting senior data professionals Choosing the IC route vs the management route Managing junior data professionals Talking to senior stakeholders and PMs as a junior The importance of hiring juniors What skills do data scientist managers need to get hired? How juniors that are just starting out can set themselves apart from the competition Asking senior colleagues for help and the rubber duck channel The challenges of the head of data Conclusion Links: Jobs at Gloss Genius: https://boards.greenhouse.io/glossgenius ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html
Hugo speakswith Katie Bauer (https://twitter.com/imightbemary) about her time working in data science at both Twitter and Reddit. At the time of recording, Katie was a data science manager at Twitter and prior to that, a founding member of the data team at Reddit. She's now Head of Data Science at Gloss Genius so congrats on the new job, Katie! In this conversation, we dive into what type of challenges social media companies face that data science is equipped to solve: in doing so, we traverse the difference and similarities in companies such as Twitter and Reddit, the major differences in being an early member of a data team and joining an established data function at a larger organization, the supreme importance of robust measurement and telemetry in data science, along with the mixed incentives for career data scientists, such as building flashy new things instead of maintaining existing infrastructure. I've always found conversations with Katie to be a treasure trove of insights into data science and machine learning practice, along with key learnings about data science management. In a word, Katie helps me to understand our space better. In this conversation, she told me that one important function data science can serve in any organization is creating a shared context for lots of different people in the org. We dive deep into what this actually means, how it can play out, traversing the world of dashboards, metric stores, feature stores, machine learning products, the need for top-down support, and much, much more.
College truly is an investment, often at least one of hundred thousand dollars and sometimes quite a bit more. As a parent, you're willing to help your teen with this investment because you know college can set them on the path toward a successful, independent, happy adult life. A significant part of that happiness is finding the right college major that leads to a best-fit career path. In this week's podcast, I sit down with Katie Bauer, the strategic partnership coordinator for Lakota Local Schools. We discuss how to cultivate experiences that will help your teen hone in on the right major for their future career.EPISODE NOTESKatie Bauer, the strategic partnership coordinator for Lakota local schools in the Greater Cincinnati, Ohio area, has worked with thousands of families throughout her career and recognizes the importance of guiding students into one of the four E's- employment, enlistment, enrollment, or entrepreneurship - for after high school graduation. Through her work, Katie helps students figure out which track best fits them, what will take them in the right direction for their future, and how to graduate high school with a purpose.A key component of determining the right path is providing students with up-close curated experiences. Through her work, Katie helps connect students with real-world experiences so they can evaluate careers for alignment to their personal wiring, values, and aptitudes. In this episode, Bauer shares insights into college and career readiness that will help your teen even if your school distinct doesn't have a “Real World Learning” initiative. You'll leave this episode being able to help your teen curate their own experiences and have tips for them to stand out from other students. Highlights The WHY behind Lakota's real-world learning programmingThe VALUE of any career exploration experienceHow students can find these opportunities via the district or their own personal networksThe 4 E's and graduating with a purposeHow real world experiences can help your teen find their post-graduation planWhat will help your teen stand out in securing job shadows and internshipsMeet Our GuestKatie Bauer's journey to traditional K-12 education was a little bit different than most. After graduating from undergrad with a BA in Strategic Communications from THE Ohio State University, she began a career in higher education. After spending many years working in admissions, she worked on a grant program through the state of Ohio called ‘Tech Prep', which aligned career technical education to industry certifications and early college credit. Along the way, Katie earned a Master's in Corporate and Strategic Communications from Ashland University. Through her work with the state and other programming, she learned about Lakota's Local School District's goals for the program to expand, and the rest is history! Bauer truly enjoys helping students learn more about themselves and In September, I'm hosting my complimentary parent masterclass, four common mistakes to avoid when choosing a college major. This is the final time this year it will be offered. Join me to identify the four mistakes strategies to avoid them and the proven path to picking a major on time without limiting options. Go to flourishcoaching co.com to learn more, or grab your spot. I'll see you soon. Join me in my complimentary September masterclass 4 common mistakes to avoid when choosing college major. I'll help your team get on the path to making informed choices that open doors as well as saving your family both time & money. For anyone who attends live, I have a special template that will empower your team when communicating with colleges. Visit flourishcoachingco.com to grab a spot before the opportunity is gone.
Katie was a founding member of Reddit's data science team and, currently, as Twitter's Data Science Manager, she leads the company's infrastructure data science and analytics organization. In this conversation with Tristan and Julia, Katie explores how, as a manager, to help data people (especially those new to the field!) do their best work. For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com. The Analytics Engineering Podcast is sponsored by dbt Labs.
Vancouver resident Katie Bauer offers her thoughts on the race. https://bit.ly/3Pk8AqT #Opinion #LetterToTheEditor #Commentary #katieBauer #ClarkCountyCouncil #District2 #Aug2PrimaryElection #Voters #Candidates #MichelleBelkot #KimHamlik #ClarkCountyBoardOfHealth #VancouverWa #ClarkCountyWa #ClarkCountyNews #ClarkCountyToday
https://www.patreon.com/datameshradio (Data Mesh Radio Patreon) - get access to interviews well before they are released Episode list and links to all available episode transcripts (most interviews from #32 on) https://docs.google.com/spreadsheets/d/1ZmCIinVgIm0xjIVFpL9jMtCiOlBQ7LbvLmtmb0FKcQc/edit?usp=sharing (here) Provided as a free resource by DataStax https://www.datastax.com/products/datastax-astra?utm_source=DataMeshRadio (AstraDB); George Trujillo's contact info: email (george.trujillo@datastax.com) and https://www.linkedin.com/in/georgetrujillo/ (LinkedIn) Transcript for this episode (https://docs.google.com/document/d/1F1bpl2wQkPuqqd1rhsT6IoK_ZkmOY9BhMGJd04UYj4A/edit?usp=sharing (link)) provided by Starburst. See their Data Mesh Summit recordings https://www.starburst.io/learn/events-webinars/datanova-on-demand/?datameshradio (here) and their great data mesh resource center https://www.starburst.io/info/distributed-data-mesh-resource-center/?datameshradio (here) In this episode, Scott interviewed Katie Bauer, a Data Science Manager at Twitter in their Core-Tech group. To be clear she was not on representing Twitter, only her own opinions. The main topic of discussion was how to measure the value and success of your data projects/implementations. Some very useful advice from Katie that can feel a bit obvious when said but is VERY often and easily overlooked: measure for what would make you drive actions. If getting a 10x higher than expected or 90% below expected result isn't going to change your decision, while it may be interesting information, is it really important? If not, don't waste the time to measure it. Especially early on in your data measurement maturity. The point is also to get to an objective evaluation, not overly precise measurements. Set yourself up to improve and iterate. Don't make this hard on yourself. She also gave the pithy statement: what is valuable is not necessarily valued. Katie has a cake analogy that plays into data maturity well. Think about your need and the other person's capability regarding making a cake. Do you need a fancy cake for wedding or is this for a 3 year old's birthday party? One, you probably want to be special. One, if it vaguely resembles something from TV and tastes decent, the consumer will probably be happy. Is the other person capable of making a super fancy layered red velvet cheesecake or is a cake mix in a box probably more up their alley. How mature are the parties on creating measurement data and how mature or advanced do you need the output to be? Katie started the conversation talking about some survivorship bias / other biased ways of measuring. Often, she has seen throughout her career that people having success seek to prove their success via metrics instead of find the metrics that matter the most. That has some pretty obvious flaws so we need to move forward towards better measurement practices. For Katie, measuring the value of data science is pretty meta. Katie recommends starting out with some really easy measurements around engagement and usage. If it's a platform, what are your daily active users, weekly active users, and/or monthly active users - and what is the actual most useful metric? Should people actually be leveraging your project daily? Think about what is your addressable market and what percent of that market you have. And NPS (net promoter score) is a very lagging indicator. When thinking about metrics, there are two things that really stand out to Katie: first, what is your useful granularity? Don't get overly precise if you don't need to. You want an objective evaluation and anything past that can become overkill, which has an inherent cost. And second, what is your useful time-scale? Is this on a micro-scale, where the task should take 5min to complete so a difference of 5min is a big deal? Or is it a much longer time scale? When thinking about what to measure, ask yourself what does your company value. Is it shipping,
Vancouver resident Katie Bauer discusses the Vancouver School District's plan to open COVID testing sites on five school campuses. https://loom.ly/A-_eL1c #VancouverPublicSchools #VancouverSchoolDistrict #LetterToTheEditor #Opinion #Commentary #COVID19 #TestingSites #EmbryHealth #VancouverWa #ClarkCountyWa #ClarkCountyNews #ClarkCountyToday
Vancouver resident Katie Bauer discusses procedures in the Vancouver School District to address COVID-19. https://loom.ly/_XdKbR8 #Opinion #LetterToTheEditor #KatieBauer #VancouverSchoolDistrict #VancouverPublicSchools #COVID19 #Masks #PCRTesting #Parents #Students #VancouverWa #ClarkCountyWa #ClarkCountyNews #ClarkCountyToday
In this episode the boys discuss the absolute juggernaut that is the BUFFALO CHICKEN SLICE! We also go LIVE to Russia to hear what our good friend Mike Schlapp thinks about Buffalo Chicken Pizza in a new segment we call "Schlapp From Russia"! Also, we get to hear from some of our closest friends, and fans of the show about what Buffalo Chicken Slices means to them! Big thanks to Mike Schlapp, Katie Bauer, Brian Bunce, and Mark Eriksen!FOLLOW US:Twitter: @guytaliansInstagram: @guytalianseatingitalianPatreon: www.patreon.com/guytaliansGmail: guytalianseatingitalian@gmail.com
Game of Thrones is back on Sunday, so it's time for the very first Texan Thrones podcast. Audio editor JT Lindsey talks with editor-in-chief Liza Anderson, photo editor Katie Bauer and senior sports reporter Cameron Parker about the hottest questions in Westeros. Who's gonna take the Iron Throne? Could Varys be a... satisfying... partner? And more!