Resume

Joined as employee number one at a startup whose core product is measurement — permissioned intent signals from engaged users that outperform the lagging behavioral data dominating ad targeting today. Built the entire technical and analytical foundation needed to prove and deliver that value proposition.

• Built the full backend and analytics stack solo. Backend services platform, analytics infrastructure, dbt/DuckDB data warehouse, Quarto dashboards, and GKE/GCE cloud deployment with CI/CD — all from scratch.
• Rooted company strategy in measurable lifecycle economics. Applied CLV frameworks before founding to turn an abstract thesis into a concrete, testable claim — and defined the metrics needed to prove it.
• Architected a platform that made new services trivial to build. A transport-agnostic FaaS framework with 13+ reusable modules (async PostgreSQL, circuit-breaking, HTTP clients) reduced new service build time to under a day — proven by an SKAN postback ingestion service and an MCP server.
• Delivered early unit economics visibility. Dagster orchestration over a warehouse covering costs, user behavior, and acquisition performance, plus an MCP server giving business users natural-language access to metrics without SQL.
• Prototyped AI conversation guidance via soft state machines. Replaced rigid scripted flows with probabilistic state transitions, producing more realistic conversations and measurably higher engagement.
• Ran Meta user acquisition end-to-end. Expanded into new Comscore geographies, hit industry benchmark CPRs within weeks through systematic creative testing, and fixed upper-funnel conversion leaks.

Joined a fintech startup as a founding engineer to build core fraud detection infrastructure — delivering a production-ready rules engine and API layer before determining the role wasn’t aligned with my trajectory as a data and analytics leader.

• Built a policy-driven fraud detection engine for enterprise scale. A service that generates Drools DRL rules dynamically from JSON definitions lets financial institutions encode their own policies without engineering involvement; a companion classification service evaluates complex multi-rule transactions in under 10 milliseconds.
• Delivered the backend API gateway and integration layer. Built in Python with PostgreSQL, connecting the front end to the rules engine and leaving the system ready for client onboarding.

Sole data scientist at a 20-person AI gaming startup — brought in as a contractor and converted to full-time based on results — responsible for building the company’s measurement capability from zero and translating data into product decisions for the CEO.

• Built the measurement foundation where none existed. Defined telemetry specifications, selected and onboarded analytics vendors (Amplitude, Statsig), and built the pipelines that gave the company its first visibility into user behavior and product performance.
• Improved first-user experience through systematic experimentation. A/B and bandit-style tests on onboarding and game design led to a simplified FUE flow with materially better completion and engagement rates.
• Identified and activated the core user base. Behavioral analysis surfaced the highest-value users; a user council channeled their feedback directly into the product roadmap.

Promoted four levels in three years (Manager → Senior Director), ultimately leading business intelligence, marketing analytics, and data science while on the leadership team of a 250-person organization — responsible for the measurement systems that shaped product and marketing decisions at EA Mobile scale.

• Saved $100M in marketing spend at a major game launch. Identified and demonstrated that the incumbent forecasting methodology would produce bad decisions, convened a cross-functional team, and implemented a transition state model for cohort growth forecasting as an R package.
• Turned re-engagement marketing from a cost center into a profit driver. An embedded analytics team transformed campaigns from money-losing giveaways into programs generating 200% ROI through continuous measurement and improvement cycles.
• Grew revenue by 5%+ through portfolio-level budget optimization. Analysis revealed reallocation opportunities across acquisition channels — a significant impact on a budget in the tens of millions.

• Cut marketing analysis effort in half. Led a cross-functional modernization of the BI practice, migrating from Hive/Hadoop to a scalable cloud data warehouse with analytics-friendly schemas.
• Navigated Apple’s ATT initiative to protect acquisition budgets. Built new SKAdNetwork pipelines and analytical strategies that maintained iOS advertising budgets while competitors pulled back.

• Transformed analysts from order-takers into strategic partners. Created space for analysts to explore beyond PM requests — leading to techniques like fixed-effects models that surfaced insights PMs would never have thought to request.

Led cross-functional data science teams across product and engineering, steering through written technical leadership — defining scope, acceptance criteria, and strategic direction in prose while delivering measurable improvements to search and content systems.

• Rescued a broken related search project. Inherited a system returning “iPhone 4” for “iPhone” queries after six months of development. Two months after redefining acceptance criteria, automating the build, and purging stale data, the system was ready for deployment on a product targeted at $500K+ annual revenue.
• Reduced vertical search site build time from three months to three days. Directed development of a tool automating index construction for narrow-topic search sites.
• Introduced Bayesian A/B testing where no testing capability existed. Built the company’s first mechanism for measuring product improvements.

• Transformed an analytics team into a delivery-oriented data science team. Adopted Scrum and built GitLab CI/CD pipelines to increase delivery cadence.
• Opened digital marketing to data science. Championed a keyword bidding project that produced automated auction data extraction and bid adjustment within two months.
• Built content moderation tooling at scale. A word-vector classifier for out-of-policy text let editors focus attention where it was most needed.

Selected for the Analytics Innovation Centre — a small group assembled for rapid iteration on the company’s digital transformation agenda — and worked directly with the executive committee to shape strategy.

• Defined requirements and built initial prototypes for Veracity, the company’s marquee data platform connecting business consumers and suppliers.

Led the west coast analytics group in a first management role, combining technical leadership on large-scale energy data problems with business development and direct client delivery for major utilities and grid operators.

• Estimated peak savings for a CPUC energy efficiency program across 40,000+ utility customers using years of hourly interval data distributed across a Hadoop cluster.
• Built a short-term renewable generation forecasting model operating at five-minute intervals to reduce grid reliance on fast-response reserves.
• Developed a discrete choice model for light bulb market shares to estimate counter-factual baselines for residential lighting programs — producing rigorous net-to-gross ratios.
• Led EV adopter identification for CenterPoint Energy, combining early adopter characteristics with travel survey data to target geographic concentrations.

Built simulation software and estimated behavioral models for regional and statewide transportation planning projects across the US, with several supporting successful federal New Starts funding applications.

• Developed one of the first discrete choice trip distribution models for the Salt Lake City regional travel demand model, replacing the gravity-based approach and supporting a successful New Starts application.
• Lead programmer on the Ohio statewide travel demand model, simulating long-distance travel for over 20 million persons using distributed computing.

Supported development of the Chicago region’s 20-year long-range transportation plan through database design, GIS visualization, and travel demand model interpretation — an early foundation in the analytical and computational methods that have defined the rest of the career.