Data Scientist- Platform Integrity

About Sleeper

Sleeper is a sports-focused games platform with messaging at its core. We are a young and energetic company, fueled by a passion for sports and a drive for innovation. Our mission is to create a digital playground for sports fans and their friends to hang out. We bring people together over sports.

About the Role

At Sleeper, we’re building the most engaging and trusted fantasy sports experience in the world, This role sits right at the intersection of growth, product, and platform integrity. As a Data Scientist focused on Risk and User Experience, you’ll shape how millions of users onboard, interact, and transact on our platform.

You’ll go beyond dashboards, designing the systems that help us understand player behavior in real time, detect fraud before it happens, and create seamless experiences that don’t get in the user’s way. From instrumenting event-level data to building models that identify suspicious activity, your work will directly influence how we scale safely and intelligently.

This is a highly cross-functional role where you’ll partner closely with product, engineering, and operations to turn data into action. You’ll help define what “good” looks like across the user journey, build the infrastructure to measure it, and continuously refine our systems as the landscape evolves.

If you’re excited about solving complex, high-impact problems in a fast-moving environment, this is your chance to build from the ground up and make a meaningful impact on a rapidly growing gaming platform.

What You’ll Do

• Driving Growth and User Experience

  • Collaborate with product leaders to optimize our onboarding funnel to identify friction and areas for improvement

  • Build scalable analytics systems for continuous evaluation of user journeys and defining key metrics

• Building Data Foundation

  • Partner with engineering to implement real-time event tracking (Firebase, Amplitude etc)

  • Define schemas and instrumentation for user activity (account creation, sessions, device/IP data etc)

• Develop Risk/Integrity Insights

  • Collaborate on systems that balance user friction with platform integrity

  • Build analytical frameworks to surface signals that inform adaptive user flows (dynamic verification requirements etc)

  • Establish prevalence measurement methodologies to quantify fraudulent activities on the platform

  • Partner with our operations teams to triage and mitigate any ongoing threats to the platform

• Advanced Analytics

  • Classify transaction risk (payment method, account-level signals)

  • Apply clustering, anomaly detection etc to large scale behavioral data

  • Continuously evaluate implemented systems and iterate based on shifting market trends

Must-Have Qualifications

• 4+ years of industry experience in data science, economics, analytics, or machine learning engineering

• Advanced Degree in computer science, statistics, or a related field

• Proficiency in scripting languages (Python, R, or similar) and big data query/processing languages and tools such as SQL, Hive, Spark, and Airflow

• Experience building or working with event-based analytics systems

• Familiarity with machine learning methods for classification, clustering, or anomaly detection

• Ability to work cross-functionally with engineering and product

Nice-to-Have Experience

• Experience working in Fraud/Risk/Trust & Safety teams

• Experience developing internal tooling for analytics, operations, or user lifecycle workflows (e.g., onboarding, review systems, or risk signals), using platforms like Retool, Appsmith, or comparable frameworks

• Experience working in real money gaming or other high-velocity transaction environments.

• Comfortable writing light JavaScript in data/UI workflows

Benefits

• Competitive salary, equity

• Comprehensive medical, dental, and vision insurance

• 401(k)

• Flexible working hours and remote work options

• Opportunities for career advancement

• Unlimited PTO

What We Offer

Sleeper believes in quality over quantity, and intentionally keeps our team small as a result. In past roles, we found it very hard to make a big impact when companies grow too large in size, which has a detrimental effect on the product and the impact any single individual can have. Our team includes designers, engineers, produ