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Ep 47: What It Takes to Productize Next-Gen AI on a Global Scale
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What does it take to turn the latest advances in AI into products that deliver business impact at Walmart levels of global scale?
Srujana Kaddevarmuth is the Senior Director of Data & Machine Learning Programs at Walmart Global Tech. Her team drives data strategy and grapples with data science productization every day. With millions of employees, hundreds of millions of customers, and petabytes of data at any given moment, Walmart offers some unique lessons in the complexities of building teams, processes, and products to effectively leverage AI at scale.
In this season finale episode, Srujana shares a few of those lessons, along with her perspective on nonlinear career paths, organizational collaboration and alignment, and her ongoing fascination with what’s next. Plus, she dives into her passion for fostering diversity in data science and tech, sharing strategies leaders can implement to help bring more women into the field.
We discuss:
- How a research background can inform leadership style
- MLOps best practices for scale
- Forming mutually beneficial partnerships between business stakeholders and data science teams
Stay tuned for a whole new season of Data Science Leaders coming soon! We're just getting started.
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Srujana Kaddevarmuth is the Senior Director of Data & Machine Learning Programs at Walmart Global Tech. Her team drives data strategy and grapples with data science productization every day. With millions of employees, hundreds of millions of customers, and petabytes of data at any given moment, Walmart offers some unique lessons in the complexities of building teams, processes, and products to effectively leverage AI at scale.
In this season finale episode, Srujana shares a few of those lessons, along with her perspective on nonlinear career paths, organizational collaboration and alignment, and her ongoing fascination with what’s next. Plus, she dives into her passion for fostering diversity in data science and tech, sharing strategies leaders can implement to help bring more women into the field.
We discuss:
- How a research background can inform leadership style
- MLOps best practices for scale
- Forming mutually beneficial partnerships between business stakeholders and data science teams
Stay tuned for a whole new season of Data Science Leaders coming soon! We're just getting started.
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