Lead Analyst, Player Analytics

Rush Street Interactive

1d•$100,000 - $140,000•Remote

About The Position

Rush Street Interactive (NYSE: RSI) is a market leader in online casino and sports betting, currently operating real-money gaming with our brands: BetRivers.com, PlaySugarHouse.com, and RushBet.co. We’re building bridges between online, social and land-based gaming businesses to create amazing, integrated experiences that keep players in the game. We’re looking for a Lead Analyst to own growth and player behavior analytics across our sportsbook, casino, and poker products. This is a high-visibility, self-directed role that sits at the intersection of analytics and business strategy. You’ll partner closely with Revenue Operations, Marketing, Product, and VIP to surface insights that directly drive player engagement and retention. This role goes beyond reporting and dashboarding, emphasizing analytical problem-solving, business partnership, and data-driven recommendations. The right candidate has strong analytical instincts, comfort with ML tooling, and a habit of using AI to push work further and faster. You'll operate with autonomy, identifying the right questions, building the right frameworks, and turning analysis into recommendations stakeholders can act on.

Requirements

3+ years in analytics, ideally within gaming, sports betting, or a consumer product with meaningful behavioral data.
Bachelor’s degree in mathematics, Economics, Engineering, Computer Science, or a related quantitative field preferred or equivalent relevant experience.
You have strong SQL fundamentals, with a command of advanced concepts like window functions, CTEs, and complex aggregations.
You are comfortable working directly in Snowflake, writing efficient queries against large datasets.
You are proven at working cross-functionally and can distill complex analysis into clear narratives and actionable recommendations for non-technical audiences.
You bring a solid understanding of A/B testing and experimental design, including statistical significance and translating test results into business context.
You have experience with funnel and cohort analysis, including modeling player lifecycle stages, retention curves, and engagement funnels.
You have working knowledge of ML concepts and hands-on experience applying AI tools to analytics workflows.

Nice To Haves

Familiarity with dbt transformation workflows and model structuring preferred.
Python proficiency, whether for analysis, automation, or lightweight ML work preferred.
Working knowledge of segmentation models, propensity scoring, churn prediction, or LTV modeling preferred.
Experience in gaming or iGaming, including familiarity with sportsbook, casino, or poker product mechanics and player economics preferred.
Experience with incentive or promotion analytics is also a plus.

Responsibilities

Partner with Revenue Operations, Marketing, Product and VIP to prioritize and execute analytics initiatives focused on player growth and long-term retention.
Manage end-to-end analytics on bonus programs- measuring performance, developing engagement strategies, and optimizing structures for both player value and ROI.
Analyze in-platform behavior across products to uncover engagement patterns, friction points, and monetization opportunities. Translate findings into personalization strategies and product recommendations.
Apply ML techniques and AI tools to accelerate insight generation, build predictive models, and continuously raise the ceiling of what the analytics function can deliver.