In this episode, guest Shalini Agarwal sits down with TDS to discuss ways of automating repetitive tasks, how we need more data scientists to make our applications smarter; however, we can make them more efficient and accomplish more with data scientists by having automated workflows and tools. These tools can be used by non-data scientists to leverage the established workflows and remove the repetitive tasks from the mountain of tasks expected from a data scientist. Shalini Agarwal is the Director of Engineering at LinkedIn, responsible for building core experience of Sales Solutions enterprise product. Before this, she was responsible for delivering scalable Search and Data Applications while managing a global team at LinkedIn. Shalini spent nearly a decade at eBay where she shaped buyer experience and transformed her career from individual contributor to management. She is leading LinkedIn’s REACH apprenticeship program since its inception, a program to hire talent coming from non-linear pathways to LinkedIn’s engineering team. She has been part of Women in Tech programs for over 10 years. Her passion lies in building great software, business applications, and empowering women.

Shalini Agarwal

https://www.linkedin.com/in/shalini-agarwal-5b735b2/ 

The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.

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