Data Scientist, Risk & Trading

Employment Type: Full-Time Location Type: Remote

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About Sleeper

Sleeper is one of the fastest-growing sports platforms in the US. We build free-to-play fantasy titles and real-money Daily Fantasy Sports (DFS) games across the NFL, NBA/WNBA, MLB, NHL, EU football, and more. Our Risk & Trading team safeguards game integrity and optimizes profitability through data-driven pricing and exposure management.

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What You’ll Be Doing

• Feature Engineering & Model Tuning: Own the pipelines that transform raw bet, player, and market data into features for our pricing and exposure models (BigQuery + SQLX, Python, Pandas).
• Predictive Modeling: Train, validate, and deploy supervised and probabilistic models that forecast player performance, market volatility, and user value.
• Guardrail Automation: Ship rule-based limiters and anomaly-detection jobs that run every few seconds, flagging and throttling outlier exposure before it becomes tail risk.
• Dashboards & Alerting: Build Grafana dashboards and SQLX reports that surface live liability, promo uptake, and top-line KPIs to trading and exec stakeholders.
• Light On-Call Rotation: During peak sports windows, respond to automated alerts and, if necessary, execute a manual override (price suspension / limit change). (Less than 2 hours/week on average).
• Cross-Functional Collaboration: Pair with Backend & Data Engineers to productionize models, and with Product to iterate on game mechanics and promos.

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Who You Are

• 3-5 years in data science, machine learning, or quant research; comfortable owning end-to-end projects.
• Fluent in Python, SQL, and modern ML tooling (scikit-learn, XGBoost, Airflow or similar).
• Familiar with sports data and the economics of fantasy / sportsbook markets; a plus if you’ve built pricing or risk models.
• Systems thinker who anticipates failure modes and edge cases in real-time environments.
• Willing to flex hours around major game slates; we’re a remote-first team and optimize schedules for coverage & work-life balance.

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Nice-to-Haves

• Experience with BigQuery, Looker, dbt, or similar analytics stacks.
• Exposure to real-time streams (Kafka, Pub/Sub) and event-driven architectures.
• Prior work building user-level segmentation or LTV models.

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Compensation

Salary Range (US): $90,000 – $175,000 USD

• The final offer considers experience, skills, and market data.
• Includes equity and benefits.

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Benefits

• Competitive salary and stock options.
• Comprehensive health, dental, and vision insurance.
• 401(k).
• Flexible working hours and remote-first culture.
• Clear paths for career growth and leadership.

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Company Information

Sleeper believes in quality over quantity, and intentionally keeps our team small. Our team includes designers, engineers, product experts, and finance & operations professionals focused on connecting people over sports. We believe in fair and equitable pay.

Equal Employment Opportunity: Sleeper provides equal employment opportunities to all applicants and employees without regard to race, color, creed, religion, sex, sexual orientation, gender identity, marital status, citizenship status, age, national origin, ancestry, disability, veteran status, or any other legally protected status.