In this episode, Jai and I discuss the nuances of building a career in data science. From his start as a product manager to his current role leading a team, Jai provides a detailed overview of the data science landscape. He discusses key topics such as a data science career trajectory, managing remote teams, the distinction between analytics and data science, and predictive versus causal modeling. The video also includes practical advice for job interviews, insights on individual contributor versus manager roles, and thoughts on Python, R, and generative AI's impact on the field.

Where to find Jai:
LinkedIn: https://www.linkedin.com/in/jaibansal/

Where to find Ida

Website: https://idajohnsson.com/
LinkedIn: https://www.linkedin.com/in/ida-johnsson/
X: https://twitter.com/IdaBJohnsson

Timestamps:

00:00 Preview
00:58 Intro
02:08 Product manager as a first job
03:25 Data science career trajectory
05:08 Managing a team
05:37 Thoughts on remote work
08:58 The role of a competent manager in a remote setting
09:55 What Jai and his team work on
13:39 Jai's team
14:38 Common interview mistakes
17:28 Common interview questions
22:02 Thoughts on IC vs. manager work
24:36 Is analytics the same as data science?
26:03 Predictive vs. causal modeling
28:14 Advice for junior data scientists
29:17 Python, R, and generative AI
32:28 Jai's career plans
33:18 Centralized vs. embedded data science teams
35:33 Navigating the job market

Reach out to me at www.idajohnsson.com