A data scientist who blends statistical thinking, machine learning and clear storytelling to turn complex systems into decisions people can act on.
The best analysis feels inevitable after you see it. My work focuses on making that path from messy evidence to confident action visible.
Built a probabilistic forecasting workflow that combined historical seasonality, promotional signals and external features. The output was designed for planners, not just model evaluation.
Mapped behavioral patterns into a calibrated risk score and surfaced the why behind each prediction so retention teams could prioritize meaningful interventions.
Designed a reproducible analytics pipeline that unified disconnected sources, exposed quality checks and gave stakeholders a faster path from question to evidence.
Turn an ambiguous request into a measurable decision problem.
Profile sources, test assumptions and find the shape of the data.
Choose the simplest rigorous method that earns the answer.
Deliver the evidence in a form that changes the next decision.
Leading experimentation, predictive analytics and measurement design across high-impact product questions.
Built forecasting and classification systems while partnering directly with operations and strategy teams.
Started with exploratory analysis and grew into end-to-end model development, deployment and decision communication.