Senior Data Scientist, ML (Brokerage)

Job Description

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. About the team + role We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. The Brokerage Data Science team uses data to inform automated modeling decisions and generate insights that guide product and business strategy. The team works closely with product, engineering, and operations partners to improve how customers engage with Robinhood’s platform. You’ll contribute to shaping personalized product experiences that support customers throughout their investing journey! As a Senior Data Scientist, ML , you will lead the development of recommendation systems for prediction markets, one of Robinhood’s fastest-growing areas. You will work closely with product managers and engineers to identify opportunities for personalization, design modeling approaches, and implement solutions that improve customer engagement. This role starts with building personalization for prediction markets and will expand to additional product surfaces as the strategy evolves. This role is based in our Menlo Park, CA and New York, NY office(s), with in-person attendance expected at least 3 days per week. At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams. What you’ll do Build and improve recommendation system algorithms to personalize customer experiences across prediction markets and other product surfaces Partner with product managers to identify areas for personalization and define measurable success criteria Develop features and models that improve relevance and user interaction with our prediction markets offerings Collaborate with software and machine learning engineers to design and implement scalable feature pipelines and the ranking systems Design and run experiments to evaluate model performance and measure incremental impact on

Required Skills