Data Scientist (Risk and Trading, Daily Fantasy Sports)

Join Sleeper, a leading platform in Daily Fantasy Sports (DFS), as a Data Scientist specializing in risk and trading. In this role, you will support risk and liability management, develop predictive models, conduct data analysis, and automate risk and trading processes. You will work closely with product and engineering teams to enhance personalization within the DFS ecosystem. Ideal candidates have extensive experience in DFS or sports betting, a background in data science or mathematics/statistics, and are comfortable working with large data sets and real-time sports data feeds.

• Support risk and liability management for Sleeper’s DFS operations through data analysis and modeling.
• Develop predictive models and algorithms to understand Sleeper’s real-time liability and risk exposure.
• Automate risk and trading processes to scale for growth in users, sports, and markets.
• In-depth knowledge of DFS, sports betting, player props, handicapping, expected value, and closing line value. Ideal candidates have extensive experience with high volumes of DFS/sports betting and real money games, either as a trader, +EV bettor, and/or oddsmaker
• Proactive – ready to hit the ground running; excited about the idea of building out processes from scratch, and not afraid to break the “sports trading mold”, challenging how the industry has historically approached risk management and trading
• Background in computer science, data science, machine learning, mathematics/statistics, or a similar field with related experience. Comfortable working with and analyzing large data sets
• Experience with player performance metrics, game outcome predictions, in-game event modeling, as well as working with real-time sports data feeds and APIs
• Comfortable working “off hours” to align with peaks in the sports calendar. This will often include nights and weekends. We are generally quite flexible and will work with you to ensure an appropriate work/life balance is molded around game schedules
• Knowledge of SQL, Python, and/or related software/tools, and familiarity in working with databases, data warehouses, data visualizations and report building