Sikha started her career as a data scientist. Then, fueled by her growing interest in machine learning, Sikha jumped on a project to build BuzzFeed's recommendation system teaching herself machine learning while on the job.

This is what I find fascinating about careers in tech. You create career leaps when you sign up for your company's next big bet - even if you don't have full experience, you learn and push yourself while building. Sikha volunteered, showed up, and delivered. Wahoo!

We also discussed how to find (and fail at) work life balance, her experience being part of the mass layoff at Twitter, and what excites her about her new role.

Come hear Sikha's money and career journey as a machine learning architect!

0:00: Intro 4:00 🤔 Do you need to be good at match to become a data scientist? 5:50 Life satisfaction == career satisfaction 11:10 Lessons learned when job didn't match expectations 14:44 💼 How to filter for new company/opportunities 18:20 📊 #datascience vs #machinelearning 21:01 Building recommendation system @BuzzFeed 22:15 How to learn machine learning (resources) 24:45 Career progression leading to higher net worth 28:50 Interest in #generativeai 32:57 Difference in startup vs big tech DS culture 35:02 😮 Getting laid off from @twitter 38:35 Machine learning architect at Snowflake