Metrics, experiments, causal reasoning, and decisions under uncertainty.
Start a session with Marcus →“Your A/B test is significant but revenue dropped. What happened?”
Every session ends with a written report scored on these three axes, with the transcript attached so you can see what earned each mark.
Frames the decision and hypothesis clearly, defines terms, explains uncertainty plainly, and leads with the actionable conclusion.
Metric validity, experiment or causal design, data quality, statistical reasoning, model evaluation, and threat awareness appropriate to the role.
Balances rigor with practical constraints, states assumptions and limitations, and makes a calibrated recommendation under uncertainty.
Relentless STAR structure, metric definitions, and edge cases.
Customer insight, prioritization, product judgment, and execution trade-offs.
Balanced and personable — the classic on-site interview.