Project overview
Responsibilities Research historical sports data to develop causally predictive models. Work with experienced modellers and developers to implement live predictions. Utilize cutting-edge statistical techniques to improve existing models. Analyze logged model output to detect patterns and anomalies. Qualifications Substantial work experience as a quantitative analyst, and/or strong educational background in Statistics, Math, or Physics from a top-tier university. Strong Python coding skills and SQL experience. Experience with R and C++ a bonus. Ability to manage and process large data sets. Working knowledge of Linux. Great communication skills and ability to work in a team-driven environment.