#225 The Full Stack Data Scientist with Savin...

Data and AI platforms are racing toward agentic and even autonomous analytics. But the bottleneck is rarely the model—it’s data readiness: governed metrics, clear metadata, and a semantic layer machines can read. For data engineers and analysts, this shifts work from hand-built S ...  Show more

AI agents are spreading across the data and AI industry, promising to automate everything from research to outreach. At the same time, teams are learning that these tools can hallucinate, leak data, or act in surprising ways. In day-to-day work, the challenge is deciding which ta ...  Show more

Catherine Nelson, author of the new O'Reilly book, Software Engineering for Data Scientists, discusses the collaboration between data scientists and software engineers -- an increasingly common pairing on machine learning and ...

In this DSS Podcast, Anna Anisin welcomes Serg Masís, Climate and Agronomic Data Scientist at Syngenta. Serg, an expert in machine learning interpretability and responsible AI, shares his diverse background and journey into data science. He discusses the challenges of building fa ...  Show more

Sophia Rowland, Senior Product Manager at SAS, discusses her journey from data science to product management at SAS, focusing on the integration of AI and analytics. She explains the concepts of Model Ops and ML Ops, the challenges organizations face in operationaliz ...

Today on No Priors, Elad chats with Erik Bernhardsson, founder and CEO of Modal Labs, a platform simplifying ML workflows by providing a serverless infrastructure designed to streamline deployment, scaling, and development for AI engineers. Erik talks about his early work on Spot ...  Show more