San Francisco, California, United States
Most of my work has been about problems where the framework doesn't exist yet—figuring out which question is actually worth asking, building the structure to answer it, and then making something happen with the output. After studying engineering at Yale, I've worked on both sides of the customer lifecycle at Capital One: acquisition strategy for premium cards (designing campaigns, building targeting models, expanding addressable markets) and post-acquisition programs, designing policies to meet customer needs. In both cases, the job has been less about running a playbook and more about diagnosing what's broken, building the business case, and partnering across product, engineering, and risk to execute. I'm very comfortable with data analytics (SQL, Python, Snowflake), but I'm most interested in the strategy layer: what the data is telling you to do differently, and whether you can build the argument for it. The most interesting answers usually come from looking at a problem from a different angle than everyone else in the room.
•Own strategy and execution for a large-scale credit program across Capital One's flagship card products, spanning customer segmentation, risk model adoption, and cross-functional partnership with product and legal teams • Identified and built the business case for expansion into underserved customer segments, driving double-digit growth in program volume while simultaneously reducing unit risk • Led adoption of a next-generation risk decisioning model across millions of annual customer requests, enabling model-based decisioning for the first time in program history
• Owned strategy and execution for a direct mail acquisition marketing campaign for Capital One's premium card portfolio, including customer targeting, and cross-functional coordination • Designed and launched a first-of-its-kind multi-product acquisition campaign, substantially expanding the addressable market and opening net-new customer segments • Directed a large-scale marketing strategy using a novel targeting framework to maximize card profitability and minimize cannibalization of existing channels • Rebuilt the response rate forecasting model using statistical regression after diagnosing structural weaknesses in the existing process, improving accuracy meaningfully
• Conducted primary and alternative data research to support Healthcare PE investment strategy, including direct engagement with sell-side analysts and data brokers to evaluate non-traditional data sources • Built an investment primer synthesizing industry trends and alternative data landscape across healthcare private equity, delivering a framework that enabled deal teams to assess opportunities more systematically
• Led strategy and operations for a 90+ member organization, overseeing budgeting, programming, and execution, including external grant funding (NASA) • Drove growth strategy, improving recruiting, engagement, and member retention, resulting in 50% membership growth • Built partnerships with external organizations to support funding, operations, and project development
• Led development of IoT-based data collection system to analyze urban heat and public health trends • Analyzed and visualized 60+ hours of geospatial data, generating insights published in Nature Cities
• Supported national growth and expansion strategy through targeted outreach and pipeline development • Built structured datasets to improve volunteer targeting, operations, and program scalability