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Scaling Data Science Value with Cross-Functional Teams (Jayesh Govindarajan, SVP Data Science & Engineering, Salesforce)

Scaling Data Science Value with Cross-Functional Teams (Jayesh Govindarajan, SVP Data Science & Engineering, Salesforce)
Nov 9, 2021 · 37m 17s

To embed models into SaaS platforms at scale, it pays to have a cross-functional team—software engineers, UX designers, data scientists, machine learning engineers—all working together. That collaboration allows you to...

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To embed models into SaaS platforms at scale, it pays to have a cross-functional team—software engineers, UX designers, data scientists, machine learning engineers—all working together.
That collaboration allows you to tackle hard challenges around scaling models to work across hundreds of thousands of customers. And it enables you to build something that offers tremendous value across many different use cases.
Jayesh Govindarajan, SVP Data Science & Engineering at Salesforce, joins the show to share how his team makes this a reality. Plus, he talks about the priceless value of customer feedback and the three areas where data science teams should focus their efforts.
We discuss:
- Arriving at data science from a pure engineering background
- Why telemetry is no substitute for customer feedback
- Tips for embedding models into a SaaS product
- The three pillars of work for a data science team
Tune in on Apple Podcasts, Spotify, our website, or wherever you listen to podcasts.
Can’t see the links above? Just visit domino.buzz/podcast for helpful links from each episode.
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