Data Scientist, Sleeper

• 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
• 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

Desirable

• 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
• 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
• 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)
• 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
• 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