| mission | schedule | hosts |
|---|---|---|
| Humanizing the data world for the next generation | Saturdays | {Shifra Williams, Sam LaFell} |
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Now at Render, she operates at the intersection of tech, education, and connection. What energizes them most is connecting technical experts with early-career learners and creating meaningful educational experiences. Through her work across platforms, she's reached over 135K learners and contributed to projects that serve 100K+ users.
Now, as a Data Engineer, he focuses on building scalable, reliable, and efficient data systems that empower organizations to make smarter decisions. Sam works across Python, SQL, and cloud platforms like AWS and Azure to build resilient data solutions. He bridges the gap between Data Science and Engineering by building and deploying models to deliver business value. Sam believes data should be an asset, not a liability, and he's also building his own business to help organizations level up their data infrastructure.
With Saturdata, Eli ventures into new creative territory beyond the silver screen. She masterfully applies her audio storytelling expertise to the podcasting medium, crafting an engaging listening experience that transforms complex technical topics into accessible and entertaining content for audiences.
From navigating interviews to mastering SQL, Python, terminal basics, and understanding AI safety, Saturdata covers the full stack of becoming a successful data professional.
Season 1

What happens when you train an evil AI and it just lies really confidently? Joey Yudelson, AI safety researcher at Redwood Research, joins Sam and Shifra to break down why 300 people standing between us and a catastrophic AI future might not be enough, and what data folks can actually do about it.

Is your Python code held together with duct tape and prayers? Sam and Shifra untangle the spaghetti and walk you through what it actually means to write clean, maintainable data code, and which tools will get you there. From the humble origins of Pandas to the blazing speed of Polars and the SQL simplicity of DuckDB, this episode is your guide to leveling up without burning down your codebase.

Your chart is full of information. So why does no one know what it means? Sam and Shifra break down everything you need to know about data visualization and storytelling, from picking the right Python library to presenting charts your exec will actually understand. Spoiler: the pie chart doesn't make it out alive.

What if your A/B test needed 67 years to reach statistical significance? Sam found out the hard way. Join Sam and Shifra as they demystify statistical testing for the real world of data work, where the stakes are lower, the data is messier, and your stakeholders definitely do not know what a p-value is.

Think you know SQL? Sam and Shifra break down what separates a query writer from a true data thinker, from basic selects all the way to distributed systems, query plans, and the four pillars of production-ready code. Plus: why your data provider's incentives are working against you, how a 1,400-line monolith hid millions in overstated revenue, and the one approach that will save you from silent, soul-crushing data failures.

Your SQL is great. But can you actually ship? Sam and Shifra kick off Season 1 (since Saturdata is zero-indexed) by covering the unsung skills that separate someone who writes queries from someone who builds things: terminal literacy, dependency management, Git, notebooks, and why UV might be Python's best friend right now. Plus, a deep dive into Marimo, the notebook tool that fixes everything you hate about Jupyter.
Season 0

Sai Bysani shares the LinkedIn strategy that transformed his career. Learn practical tips for content creation, comment strategies, and why starting where you are beats waiting for perfection.




Join hosts Sam and Shifra as they explore the realities of data roles. Sam discusses a day in the life of a data engineer. From the glamorous perceptions to the day-to-day challenges, they discuss the skills, stakeholders, and the importance of understanding the "why" behind data projects.










