Staff Data Scientist - Algorithms

<div class="content-intro"><h2>Join us in building the future of finance.</h2> <p>Our mission is to democratize finance for all. <a href="https://www.cerulli.com/press-releases/cerulli-anticipates-124-trillion-in-wealth-will-transfer-through-2048" target="_blank">An estimated $124 trillion of assets</a> 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.</p></div><h3><strong>About the team + role</strong></h3> <p>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.</p> <p>The <strong>Incentives Data Science</strong> team sits at the intersection of Product, Marketing, Finance and Machine Learning. Our mission is to enable sustainable, data-driven growth by building modeling, measurement, and optimization systems that drive activation, retention, and revenue at scale. We partner closely with cross-functional teams across Robinhood to design, evaluate, and operationalize incentive programs that efficiently acquire, activate, and retain customers. </p> <p>As a <strong>Staff Data Scientist, Incentives</strong>, you will lead the end-to-end design, optimization, and evolution of Robinhood’s incentive systems. You’ll build predictive and causal ML models, design experimentation frameworks, and develop decisioning and allocation algorithms that directly influence how millions of users engage with Robinhood. This is a rare opportunity to own highly impactful ML systems while shaping incentive strategy at company scale!</p> <p>This role is based in our <strong>Menlo Park, CA</strong> office, with in-person attendance expected at least <strong>3 days per week</strong>.</p> <p>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.</p> <h3><strong>What you’ll do</strong></h3> <ul> <li>Build, deploy, and iterate on predictive and causal models for incentive targeting<br><br></li> <li>Design and evaluate experiments to measure incremental impact, payback, and ROI of promotional programs<br><br></li> <li>Partner cross-functionally with Product, Finance, Marketing, and Engineering to inform scalable incentive strategies<br><br></li> <li>Design and optimize incentive allocation algorithms under budget and policy constraints to maximize incremental impact<br><br></li> <li>Monitor production systems, analyze user behavior, and propose algorithmic and policy improvements<br><br></li> <li>Influence the long-term vision for growth modeling at Robinhood, including personalization and cross-sell optimization<br><br></li> </ul> <h3><strong>What you bring</strong></h3> <ul> <li>7+ years of experience applying ML in production, ideally in growth, incentives, marketplace, or personalization domains<br><br></li> <li>Proven track record owning models end-to-end — from design and development to deployment and iteration<br><br></li> <li>Deep expertise in predictive modeling ... (truncated, view full listing at source)