Data Scientist- Platform Integrity

Sleeper

9d•$130,000 - $175,000•Remote

About The Position

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.

Requirements

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 Haves

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

Responsibilities

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