Abstract: We work in an industry where a data scientist works on anything from visualization, dashboarding, EDA and business analysis to machine learning, deploying models to production and writing complex distributed algorithms. The question of who a data scientist is and going to be is one that's been debated ever since the practice started getting widespread attention. In this talk I'll go over the field, the different focus areas and how an aspiring data scientist can navigate it given their unique background.
Bio: Behrooz has been working with data in various capacities over the past 15 years. Academically he has studied mathematics and AI, working specifically on probabilistic algorithms and implementing distributed training frameworks. Professionally, he has worked for a number of startups over the past decade, focusing on computation at scale and bringing ML to various product and business problems ranging from recommender systems and distributed clustering to forecasting and production ML ecosystems.
Currently, he is managing a team of data scientists and ML engineers at Spotify working on predictive models that aim to understand the podcast space, user behavior and automated anomaly detection at scale.