About Auranova Decision Lab
We teach modern Decision Science with clarity and restraint—no hype, no gimmicks.
Story
Founded by practitioners from analytics, product, and behavioral science, Auranova Decision Lab began as a set of internal playbooks to help teams choose the next best move in ambiguous environments. Those playbooks became our curriculum—focused on adaptive Bayesian reasoning, causal structure before metrics dashboards, and the discipline to stop when data does not move the decision.
Mission
Enable professionals to make clear, confident, and ethical decisions by combining statistical evidence with human judgment.
Pedagogy
- Model humility: quantify uncertainty and act proportionally to risk.
- Evidence chains: connect data to decisions through clear causal stories.
- Practice over theory: weekly decision memos and applied projects.
- Ethics first: articulate trade-offs and distributional effects.
Team
Mira Sandell — Director of Programs
Leads curriculum design across Bayesian and forecasting tracks. Previously built experimentation platforms for B2C marketplaces.
Evan Ritchie — Principal, Causal Methods
Econometrics and uplift modeling specialist; emphasizes design before data when evaluating interventions.
Noor Valen — Behavioral Scientist
Translates cognitive science into decision checklists that teams can apply in under ten minutes.
Kai Ito — Faculty, Optimization & Risk
Focuses on portfolio and resource allocation under constraints, with transparent assumptions and sensitivity analysis.