Managing a data science function is not only about delivering analytical products and insights. It is a strategic arm of the organization's digital journey and requires tapping into the organizational data strategy, team and talent, cultural transformation, and product innovation. In this session, we will discuss top subject areas that one must not miss while managing data science functions.
1. Building blocks of managing a data science function
2. Leading data science teams and nurturing talent
3. How to build great data products
General Manager, Data Science
Saurabh Gupta is a data analytics leader, published author, and currently works with Michelin as General Manager of Data Science. At Michelin, his focus is to drive data-driven culture and bring AI transformation by building analytical products, evangelization of data tools, and stemming technology hubs. He holds a management degree from Harvard Business School and Masters from BITS Pilani. He co-authored "Practical Enterprise Data Lake Insights' ' (Apress) in 2018 to set out architectural considerations to design big data lakes for analytics consumption. Earlier, he worked with Packt to author "Advanced Oracle PL/SQL Developer's Guide" in 2016, and "Oracle Advanced PL/SQL Developer Professional Guide'' in 2012. He is a frequent speaker at conferences organized by the data and analytics user community and technical institutions.
Outside his work, storytelling is his hobby and he loves reciting experiential stories for his daughter.
Favorite quote – “Simplicity is the ultimate sophistication”
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