The Data Scientist Show

Christopher Fricker is a senior director in analytics and BI at Renaissance Learning. He started his career in finance and later became a data science consultant working with Meta, Netflix, and pre-IPO tech companies doing analytics. We talked about the mental models that helped him grow from a finance analyst to an analytics leader.

Subscribe to Daliana's newsletter on ⁠https://www.dalianaliu.blog/⁠ for more on data science and career.

Chris’ LinkedIn: https://www.linkedin.com/in/christopherfricker/

Daliana’s LinkedIn: ⁠https://www.linkedin.com/in/dalianaliu/⁠

(00:00:00) Introduction(00:01:46) How to get promoted quickly(00:08:40) Power vs authority(00:11:21) First principal thinking(00:32:34) ROI of a data team(00:40:29) How to be persuasive(00:54:52) All Data is wrong(00:56:22) How he audits the data(01:00:52) How to make someone help you at work

Daliana’s newsletter on how to find your edge in the AI age and live events: https://dalianaliu.kit.com/e0dcfc214b

Daliana interviewed her friend of 10 years, Mike Lo, on how he went from a physics PhD to Sales Engineer at Databricks, and fun stories of their friendship in LA.

Mike Lo’s Linkedin: https://www.linkedin.com/in/hellomikelo/

Daliana’s newsletter on how to navigate your career in the AI age: https://dalianaliu.kit.com/e0dcfc214b

Evelyn was an analytics manager at Amazon and now full time vlogger. We talked about how she became a vlogger, how she navigated her career after leaving Amazon, and what she learned about the creator economy.

Evelyn’s YouTube: https://www.youtube.com/@tapiocapress

Daliana's Linkedin: https://www.linkedin.com/in/dalianaliu/

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I had a fun “funeral” of this show with Tina Huang, we talked about death, afterlife, and the various transitions as content creators. Get coached by Daliana:• DS/ML Career Accelerator

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I went on Super Data Science with Jon Krohn to discuss how to accelerate your career in data science, why I paused the podcast, and how to navigate the industry's change.

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I went on Super Data Science with Jon Kron to talk about how to accelerate your career in data science, why I paused the podcast, and how to navigate the change in the industry.

Ben Rogojan, aka, Seattle data guy is an ex-Meta data engineer turned data engineering consultant and YouTuber. He has 100k followers each on YouTube and LinkedIn. We talked about how he become an independent consultant and the current state of data engineering.

- Ben’s LinkedIn: ⁠https://www.linkedin.com/in/benjaminrogojan/⁠

- Daliana’s newsletter on career growth and personal branding: ⁠https://dalianaliu.kit.com/profile⁠

⁠Hi! I'm Daliana Liu⁠ Join 20,000+ subscribers to read the career lessons from my 7-year experience at Amazon and my solo-founder journey.

Daliana interviewed 6 data scientists from her meetup in New York City. It's a unique episode where you get to hear the real frustrations of data scientists. We talked about struggles working in healthcare, finance, data quality and AI, how to advocate for yourself, and align with your managers.

Subscribe to Daliana's newsletter on ⁠www.dalianaliu.com⁠ for more on data science and career.

Daliana's Twitter: ⁠https://twitter.com/DalianaLiu⁠

Daliana’s LinkedIn: ⁠https://www.linkedin.com/in/dalianaliu/

Most experimentations fail, Kristi Angel shares her expertise on scaling experimentation and avoiding common A/B testing pitfalls. Learn five things that can help boost test velocity, designing impactful experiments, and leveraging knowledge repos. (Chapters below)

Kristi Angel’s LinkedIn: ⁠https://www.linkedin.com/in/kristiangel/

Subscribe to Daliana's newsletter on ⁠www.dalianaliu.com⁠ for more on data science and career.

Daliana's Twitter: ⁠https://twitter.com/DalianaLiu⁠

Daliana’s LinkedIn: ⁠https://www.linkedin.com/in/dalianaliu/⁠

(00:00:00) Intro

(00:01:26) Why do most experimentations fail?

(00:07:05) Mistakes in choosing metrics

(00:10:05) Is revenue a good metric?

(00:13:18) Split metrics in three ways

(00:15:10) Daliana's story with too many category breakdowns

(00:16:59) What makes the best data science team?

(00:19:24) Data scientist work in silo vs in a data science team

(00:21:15) Building a knowledge center

(00:23:40) Example of knowledge center; nuance of experimentations

(00:26:09) How many metrics and variants?

(00:30:56) How to reduce noise - CUPED

(00:33:01) Future of A/B testing

(00:38:33) Q&A: Low statistical power