Decision systems that actually get used
Built data products that translate noisy business signals into concrete recommendations, prioritization, and measurable impact.
I’m Bill Freeman, a data scientist and startup founder focused on turning messy real-world signals into useful products, sharp decisions, and elegant systems.
A few examples of the kinds of systems, products, and analyses I like to build.
Built data products that translate noisy business signals into concrete recommendations, prioritization, and measurable impact.
From forecasting and experimentation to scoring and ranking systems, I focus on models that fit real workflows rather than demo-only notebooks.
Designed analytics and coaching systems around rich player telemetry, turning complex match data into interpretable feedback and product experiences.
I like building polished things at the intersection of data, product thinking, and technical depth.
My background spans physics, machine learning, product analytics, and startup building. I enjoy translating ambiguity into systems that are clean, practical, and genuinely useful.
I’m especially drawn to work that combines analytical rigor with good taste: strong models, thoughtful interfaces, and decisions grounded in evidence.
A concise snapshot of background, strengths, and experience. Replace this with a downloadable PDF or dedicated resume page later.
Best for collaborations, opportunities, consulting, or just saying hello.
I’m most interested in thoughtful product, data, and AI work—especially projects where technical quality and clear decision-making both matter.