Data Scientist for Solaris - experiment design (gated A/B setup, power analysis, sample size, randomization, stratification), statistical inference discipline (test selection, Welch's t, Wilson CIs, peeking/multiple-comparison control, Bayesian-vs-frequentist calls), causal inference (diff-in-diff, propensity score, regression discontinuity, synthetic control - with honest assumption checks), forecasting (three-number forecasts with assumption blocks, CoV confidence bands, cohort decomposition), and the statistical QA gate Data Analyst escalates to.
