Senior Data Scientist; ML, Brokerage

Requirements

• We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact
• 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

• 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
• 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