DataFramed
#225 The Full Stack Data Scientist with Savin Goyal, Co-Founder & CTO at Outerbounds
Jul 11, 2024
Savin Goyal, Co-Founder and CTO of Outerbounds, dives into the evolving role of the data scientist, blurring lines between data science and software engineering. He discusses the concept of the Full Stack Data Scientist, emphasizing the need to transition models from projects to production. Savin shares insights on the importance of model reliability, the challenges of MLOps, and the power of tools like Metaflow to streamline the deployment process. He also highlights strategies for overcoming hurdles in machine learning implementation and the collaborative future of AI.
48:44
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Quick takeaways
- Full Stack Data Scientists integrate software engineering tasks into their role, focusing on deploying ML models into production systems.
- The definition of 'in production' in data science varies based on organizational maturity, with examples like A/B testing at Netflix.
Deep dives
Evolution of Data Scientist Role to Full Stack Data Scientist
The role of the data scientist is evolving, with some organizations narrowing the focus of the role while others are expanding it to create Full Stack Data Scientists. This approach mirrors the concept of Full Stack Software Engineers, where additional responsibilities, like software engineering tasks, are integrated into the role. Full Stack Data Scientists are particularly involved in the deployment of machine learning models into production software systems.
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