
All Things Product Data Science is your go-to newsletter for practical insights, experimentation techniques, and real-world lessons from 100+ experiments—covering everything from A/B testing to causal inference.
| Platform | Pricing | Only free issues | Publishes | Weekly | |
|---|---|---|---|---|---|
| Issues | 12 | Founded | a year ago | Last Issue | 3 months ago |
| Active | |||||

A model is only as good as your ability to measure it. This edition dives deep into the high-stakes world of online vs. offline calibration, the architecture of model-based A/B testing, and the "Million-Dollar Question": when should you t...
In product development, A/B testing is often the go-to standard. But if we work in Payments, Fraud, or Trust & Safety (T&S), we quickly realize that the familiar rules of experimentation, randomly splitting users to test UI changes fall sho...
Most experiments are time-bound. You define a test window, run it for a few days or weeks, review the results, and make a call.
In the early days of a test, a spike in metrics often feels like a win. Conversion is up. Engagement looks str...
In data-driven organizations, experimentation has become the default mechanism for informed decision-making. A/B tests, pilots, and controlled rollouts are designed to introduce rigor and objectivity into how teams decide what to build and...
The phrase “data science” often gets used as if it refers to one monolithic discipline. In reality, it is an ecosystem, a set of interconnected but distinct functions that transform raw data into business impact. Under this umbrella sit sev...
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The writers behind this newsletter.
Data science leader at Walmart with 13+ years of industry experience and 500+ experiments powering growth, funnels, and pricing decisions.
With 12+ years of experience in finance and e-commerce, I lead AI Risk Management at Amazon, where I build LLM frameworks for Anti-Money Laundering to enable safe.
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