Director of Product Data Science leading Coinbase’s Platform Data Science organization across payments, risk, identity, onboarding, customer support, experimentation, and ML/platform capabilities. Led a 20+ person org, including managers and senior ICs, partnering with Product, Engineering, Ops, and executive leadership on critical growth, risk, and product-quality decisions across the company’s core user journeys.

Selected impact:

• Built the metrics and decision framework used to manage key user journeys, helping leadership make faster, higher-confidence calls on growth, risk, and customer experience tradeoffs.

• Raised the company’s experimentation maturity by improving standards, tooling, and operating cadence, increasing both test velocity and trust in results.

• Reworked the measurement and evaluation loop for risk/restrictions, improving the speed and reliability of policy and model iteration while reducing customer friction.

• Drove nine-figure annualized business impact across payments, identity, and risk through better decision-making on fraud, conversion, and operational efficiency.

Lead Data Science & Data Engineering teams covering Coinbase Wallet, Discovery & Community, Coinbase NFT, Crypto Wallets, Coinbase Cloud, Asset Listings and Maintenance, and Staking & Protocols

Led the Support Science team to build and deploy causal inference, machine learning, and optimization models to guide the development of optimal self/assisted service support experiences for Lyft rideshare users.

Led the Safety Science team that drove experimentation of Lyft product features to deter and detect safety incidents, designed direct and indirect measures for safety, and built and deployed ML and NLP models to assess and detect safety risk in real time.

Data Science is at the core of powering Sonder’s platform for the world's first deconstructed hotel. The DS team built models and data products powering revenue forecasting, dynamic pricing and underwriting.

Led the team responsible for building Helio (https://bit.ly/2rvtpZz) - the data and machine learning engine of CircleUp - that is powering the first of its kind technology-driven investing in early-stage companies. My team was responsible for solving the most exciting and challenging data engineering and data science problems that arose from ingesting, organizing, and processing data from a multitude of messy sources and synthesizing insights and predictions from that data.