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Motorsports Sportscar Race Strategist
About the position
The GM Motorsports Program is seeking a race strategy analyst dedicated to guiding the development of race strategy tools and directly supporting teams to positively affect the outcome of Sportscar program events. GM Motorsports currently supports our teams in the IndyCar and NASCAR Series with real-time, AI/ML based race strategy tools; initial work will involve merging these existing tools/analysis techniques and adapting them to the WEC and IMSA grids. Leveraging these varied approaches and experiences across different series will give you an opportunity to be a key part in developing a cutting-edge race-strategy software for Sportscars and advance the core GM Motorsports race-strategy platform for IndyCar, NASCAR and Formula 1 series. Though a portion of the early work will focus on tool development, you will also perform strategy analysis and contribute to current IMSA and WEC events. Event support will largely consist of developing the underlying analysis to guide in-event BOP management along with maximizing race outcome through effective strategy execution. Once tools reach maturity, greater emphasis will be placed on implementation and application of real-time strategy tools. Throughout the design cycle, the role will require extensive collaboration with internal GM personnel supporting NASCAR, Formula 1 and IndyCar series, IT development and data science groups.
Responsibilities
- 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.
- 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 Monte 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.
Requirements
- Bachelor's Degree in Engineering, Physics, Mathematics, Statistics, Computer Science, Data Science, or related field.
- 7+ years of experience in a top-level motorsports series including NASCAR, IMSA, F1, IndyCar, WEC, or similar and 2+ years developing or utilizing strategy tools in top-level series.
- Intimate knowledge of motorsports race strategy tools and experience using models and performing analysis to drive strategy decisions during live race events.
- Proficient programming in Python, MATLAB, or similar language.
- Familiarity with AI/ML modeling techniques and methods being developed and applied across industry.
- Strong organization skills, forward thinking mentality, and a superb attention to detail.
- Well-developed interpersonal abilities with experience developing relationships and navigating politics across teams and sanctioning bodies. Patient and considerate with a strong desire to mentor developing engineers.
- Ability to travel 10% of the time within the United States.
Nice-to-haves
- Master's degree in a quantitative field.
- Knowledge and experience in tire modeling, construction, testing, and validation.
- Working knowledge of simulation workflows in professional motorsports organization. Experience using simulation tools to optimize vehicle performance.
- Experience with machine learning libraries.
- Experience with big data tools (e.g. Hadoop, Spark, SQL, and NoSQL Database experience).
Benefits
- Relocation benefits may be available.
