Overview
Full job description
What you’ll do: Contribute to the research, design, and implementation of predictive statistical and machine learning models across prediction markets and exchange venues Prototype and backtest models, monitor performance, and assist with optimizations. Contribute to key feature development for model efficiency Develop and maintain Python codebases in a Linux environment. Help to design and implement new pricing models and frameworks Support data pipeline and SQL database interactions for real-time models. Assist in improving trading systems and operational tools. Gain exposure to multiple sports, quantitative disciplines, and production engineering. Other duties as assigned. Skills you’ll need: Proficiency in Python (experience in R or other languages a plus). Strong interest in statistical modeling, machine learning, or predictive analytics. Familiarity with Linux and SQL databases. Ability to work in a fast-paced environment and manage multiple tasks. Interest in sports and sports analytics / sabermetrics. Strong problem-solving and communication skills. Predictable and reliable availability It’s great to see: Coursework in statistics, optimization, computer science, or related fields. Prior internship or project experience in trading, quantitative research, or software engineering. Exposure to object-oriented development, real-time systems, or algorithmic trading models. Experience with sports gambling, fantasy sports, or predictive analytics applied to sports.
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