senior-data-scientist
World-class data science skill for statistical modeling, experimentation, causal inference, and advanced analytics. Expertise in Python (NumPy, Pandas, Scikit-learn), R, SQL, statistical methods, A/B testing, time series, and business intelligence. Includes experiment design, feature engineering, model evaluation, and stakeholder communication. Use when designing experiments, building predictive models, performing causal analysis, or driving data-driven decisions.
analytics-metrics-kpi
Master metrics definition, KPI tracking, dashboarding, A/B testing, and data-driven decision making. Use data to guide product decisions.
prompt-evaluation
Prompt testing, metrics, and A/B testing frameworks
growth-experimenter
Run systematic growth experiments to increase acquisition, activation, retention, and revenue. Use when optimizing conversion funnels, running A/B tests, improving metrics, or when users mention growth, experimentation, optimization, or scaling user acquisition.
feature-flags
Feature flag patterns for controlled rollouts, A/B testing, and kill switches. Use when implementing feature toggles, gradual rollouts, canary releases, percentage-based features, user targeting, or emergency kill switches.
feature-flag-system
Implement feature flags (toggles) for controlled feature rollouts, A/B testing, canary deployments, and kill switches. Use when deploying new features gradually, testing in production, or managing feature lifecycles.
