This weekend-intensive workshop is built for data scientists who want to go beyond just “running experiments” — and start shaping product strategy through evidence-based decision-making.

Over two immersive days, you’ll gain hands-on experience in designing robust experiments, analyzing results with rigor, and translating findings into measurable business impact. Through live lectures, breakout discussions, and case-based exercises, you’ll learn not just how to run experiments, but why each design choice matters — from hypothesis framing to metric selection and trade-offs.

This program is fast-paced and practical, tailored for mid-level professionals who want to level up their experimentation craft and drive product outcomes with clarity and confidence.

In this workshop, you’ll cover:

1) Advanced experimental design — from hypothesis framing to metric definition and power analysis

2) Real-world pitfalls — peeking, selection bias, Simpson’s paradox, and multiple testing

3) Statistical analysis techniques — t-tests, non-parametric tests, and confidence interval interpretation

4) Advanced methods — sequential testing, variance reduction, multi-arm bandits, and Bayesian A/B testing

5) Communication and impact — translating results into actionable product and business insights