Data scientist working on pricing, experimentation, and customer decision systems.
I focus on turning analytical work into decisions that can be explained, measured, and improved in real operating environments.
“All models are wrong, but some are useful.”
George Box
What I bring
Current work
I work on applied data science problems in personal finance, supporting pricing, marketing targeting, and customer experience decisions through experimentation and analytical modeling.
My focus is translating analytical results into decisions that can be explained, monitored, and continuously improved in production environments.
Research background
Before moving into industry, I spent almost two decades in academic research studying cytoskeleton dynamics and actomyosin contractility, working in environments where data analysis, microscopy systems, and computational tools were central to experimentation.
This experience shaped how I approach problems today through hypothesis-driven thinking, careful interpretation of results, and awareness of uncertainty and experimental limitations.
Selected work from applied data science projects and previous academic research.