Built by practitioners, for practitioners

Three data science leaders who believe the future belongs to full-stack builders — people who can ask the right questions, validate the answers, and ship decisions.

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"AI can conduct the analysis, but it can't tell you what question to ask or whether the answer makes sense."

We met building data teams at Nextdoor, where we saw the same pattern play out over and over: brilliant product managers, engineers, and designers waiting days or weeks for data teams to answer questions they could have answered themselves — if someone had taught them how to think analytically.

So we started the Data Neighbor Podcast to share what we'd learned across Stripe, Meta, LinkedIn, Microsoft, and beyond. The conversations we had with listeners and guests made one thing clear: the demand for practical analytical training was far bigger than a podcast could serve.

AI Analyst Lab is our answer. We build courses and workshops that teach product teams to think like product data scientists — with AI as an accelerator, not a replacement for judgment.

This is NOT

A SQL/Python course. Pure AI prompt engineering. A passive learning experience.

This IS

Product data science thinking. Decision-making and influence training. Hands-on with real scenarios. Skill first, then AI, then execution.

The Team

From Stripe to Meta to Microsoft

We've built and led data teams at companies you know.

Shane Butler

Principal Data Scientist, AI Evaluations, Ontra

Principal DS at Ontra

Previously at

Stripe · Nextdoor · AppFolio · PwC

Shane is a Principal Data Scientist at Ontra leading AI evaluation strategy for product development in legal tech. He brings 10+ years of experience in product data science, causal inference, and measurement across B2B SaaS and consumer products from roles at Stripe, Nextdoor, AppFolio, and PwC. His work focuses on practical methods for evaluating AI features in production, connecting offline quality signals to real user and business outcomes. He co-hosts the Data Neighbor podcast interviewing product, data, and engineering leaders shaping next-generation analytics in AI-driven landscapes.

Sravya Madipalli

Senior Manager, Data Science, Superhuman

Sr Manager DS at Superhuman

Previously at

Microsoft · eBay · Nextdoor · Grammarly

Sravya is a Senior Manager of Data Science with 14+ years helping teams make better decisions with data. She has built and led data science and product analytics teams at Microsoft, eBay, Nextdoor, and Superhuman, collaborating closely with product, engineering, marketing, and leadership. Her expertise spans experimentation, metrics design, modeling, analytics, and translating complex user behavior into clear, actionable insights. She mentors data scientists and non-data partners to think analytically, ask sharper questions, interpret results confidently, and make decisions despite imperfect data. She brings real-world big-tech analytical frameworks adapted for modern teams using AI as a copilot.

Hai Guan

Senior Director / Head of Data, Ontra

Head of Data at Ontra

Previously at

LinkedIn · Nextdoor · Pinterest · Meta

Hai has spent 16+ years teaching data professionals, PMs, designers, and leaders to think analytically. At Nextdoor, LinkedIn, Pinterest, and Meta, he built and scaled data teams transforming how companies make product decisions. His teams drove projects that doubled user acquisition, scaled products to IPO, and launched business units becoming growth engines. He has mentored hundreds of non-data professionals to ask better questions, interpret results confidently, and make decisions without waiting for an analyst.

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Our courses teach the same frameworks we've used to drive decisions at Stripe, Nextdoor, Microsoft, and beyond.

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