Senior Data Scientist, ML (Brokerage)

Robinhood • Menlo Park, NY

1d • $146,000 - $220,000 • Hybrid

About The Position

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.

Requirements

• 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

Responsibilities

• 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

Benefits

• Challenging, high-impact work to grow your career.
• Performance-driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching.
• Best-in-class benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents.
• Lifestyle wallet — a highly flexible benefits spending account for wellness, learning, and more.
• Employer-paid life & disability insurance, fertility benefits, and mental health benefits.
• Time off to recharge including company holidays, paid time off, sick time, parental leave, and more!
• Exceptional office experience with catered meals, events, and comfortable workspaces.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed
• Number of Employees: 501-1,000 employees