Experimentation (A/B) Analyst

About This Course

An Experimentation (A/B) Analyst specializes in measuring causal impact of product/marketing changes. They design experiments with clear hypotheses, success and guardrail metrics, randomization approach, and minimum detectable effects. During execution, they validate instrumentation, ensure exposure logging is correct, and monitor issues like sample ratio mismatch or contamination. After completion, they analyze results with statistical rigor, estimate uplift and uncertainty, and interpret results for rollout decisions. A key value is preventing wrong decisions caused by noisy data or flawed setups. The role works closely with product, growth, and engineering teams and may build experimentation playbooks and standardized dashboards. Tools include SQL, Excel, experimentation platforms, and sometimes Python/R. This role suits analytically strong candidates who enjoy methodology, precision, and building trustworthy decision systems.

Key Responsibilities

• Experiment design
• hypothesis
• sample sizing (basic)
• result analysis
• guardrail metrics

Growth Path

Tools Used

Perfect For

Analysts interested in rigorous measurement

Fee Structure