Rush Street Interactive

Lead Analyst, Player Analytics

USA - Remote

Sponsorship not specified$100k-$140kDetected 8 hours ago

PythonSQLSnowflakeMachine LearningdbtA/B TestingExperimental DesignCollaborationProblem Solving

About the role

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.
This is a high-visibility, self-directed role that sits at the intersection of analytics and business strategy.
This role goes beyond reporting and dashboarding, emphasizing analytical problem-solving, business partnership, and data-driven recommendations.

Partner with Revenue Operations, Marketing, Product and VIP to prioritize and execute analytics initiatives focused on player growth and long-term retention.
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.
You bring a solid understanding of A/B testing and experimental design, including statistical significance and translating test results into business context.
Growth - we want you to develop personally as well as professionally
We are dedicated to treating everyone with respect and to support your professional and personal growth.

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 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.
As required by federal law, we provide the following notices to all prospective U.S. employees:

Bachelor's degree in mathematics, Economics, Engineering, Computer Science, or a related quantitative field preferred or equivalent relevant experience.
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.

Rush Street Interactive is an equal opportunity employer and committed to a diverse and inclusive workplace.

identity and expression, marital status, family status, lifestyle, age, culture, religion, military and veteran status, citizenship, or disability

This listing is sourced directly from Rush Street Interactive's careers page and normalized into a canonical job model.