Motorsports Sportscar Data Analyst

Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Concord, NC three times per week, at minimum. Given the need to support some live race events during weekends, this role will require the ability to work a flexible schedule.

The Role    
We are seeking a Motorsports Sportscar Data Analyst to apply data science and modeling techniques to develop and refine race strategy tools, facilitating insightful pre-race planning, split-second identification of pivotal strategy inflection points during live race events.  

What You’ll Do   

• Evolve existing AI/ML models for application in Sportscars:  refining existing python code-base where appropriate and reimagining where necessary.  

• Develop platform for running and interrogating Mote Carlo free-air simulations.  

• Create tire degradation models, refining parameters and coefficient fits for accurate future predictions.   

• Conceptualize most efficient means of conveying insights through new visualizations.  Prototype working examples and collaborate with IT and software partners to develop production implementations.  

Employ race strategy tools and standalone models to verify accuracy, understand performance, and reveal areas for future enhancement. Collaborate with IMSA and WEC teams to implement tools and derive insights for each race event.  

• Resolve true vehicle pace from track migration, traffic, energy savings strategies, tire and fuel burn effects. 

• Predict in-race and session-to-session pace variation to inform session planning and derive most effective strategy approaches. 

Collaborate with diverse technical teams across GM, GM Motorsports and GM sponsored motorsports teams to develop and support race strategy tools and provide analytic guidance.  

• Co-develop production race strategy software with data science and IT software development.  

• Work with teammates supporting other racing series to apply analysis techniques and modeling approaches to other series to validate processes and refine models.  

• Transfer learning and approaches between the series in which GM Motorsports teams compete.   

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