Data Scientist / Quant - Risk & Trading

Summary

Join Sleeper's Risk & Trading team as a Data Scientist to build and deploy machine learning models for pricing and exposure management in the fast-growing sports platform. You will be responsible for feature engineering, model tuning, predictive modeling, guardrail automation, and dashboard creation. The ideal candidate has 3-5 years of experience in data science or a related field, fluency in Python and SQL, and familiarity with sports data. Sleeper offers a competitive salary, equity, and benefits including health insurance, 401k, and flexible working hours. The role involves collaboration with other teams and light on-call rotation during peak sports seasons. Sleeper is a remote-first company that prioritizes work-life balance.

Requirements

• 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; 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

Responsibilities

• 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). < 2 hrs/wk on average
• Cross‑functional collaboration – Pair with Backend & Data Engineers to productionize models, and with Product to iterate on game mechanics and promos

Preferred Qualifications

• 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

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