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.
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 customer engagement
What you bring
- You have 5+ years of experience building recommendation systems in customer-facing products (e.g., streaming, marketplace, or on-demand platforms)
- You are proficient in Python and SQL and have strong experience with machine learning systems and production modeling
- You have experience with experimentation methods and causal inference to evaluate model performance
- You communicate clearly and collaborate effectively with product, engineering, and data science partners
- You demonstrate ownership by driving projects from concept through implementation