Motorsports Strategy Intern - Sportscar Motorsports Strategy

## The Role: GM is seeking a Sportscar Motorsports Strategy intern to perform complex analytical work supporting the GM Motorsports program. The intern will support race-strategy initiatives by applying vehicle dynamics, race engineering, and motorsports strategy principles, along with programming knowledge, to existing and future simulation tools. ## The Team: The Sportscar Motorsports Strategy team supports race-strategy and vehicle-performance decision-making across GM’s IMSA and FIA World Endurance Championship (WEC) programs. The team analyzes vehicle, tire, weather, traffic, race, and simulation data; develops and evaluates strategy models; improves simulation workflows; and works with engineers and strategists to investigate performance trends, evaluate alternatives, quantify uncertainty, and communicate technical findings. ## What You’ll Do: - Analyze race, vehicle, tire, weather, and simulation data to identify trends and performance opportunities. - Support the development, testing, and improvement of race-strategy and vehicle-performance simulation tools. - Apply engineering fundamentals, statistics, optimization, and dynamic-systems concepts to practical motorsports problems. - Develop scripts, visualizations, and analytical workflows that improve the speed, consistency, and usability of engineering decisions. - Explore appropriate applications of artificial intelligence and machine learning, including performance prediction, time-series analysis, classification, anomaly detection, parameter estimation, and surrogate modeling. - Validate analytical and machine-learning results against engineering expectations, simulation outputs, and observed race data. - Document methods, assumptions, limitations, and results, and communicate recommendations to technical and cross-functional audiences. ## Required Qualifications: - Pursuing a Bachelor’s degree in Mechanical Engineering, Aerospace Engineering, Electrical Engineering, Mathematics, Physics, Data Science, or a related field. - Expected graduation between December 2027 to June 2029. - Able to work full-time, 40 hours per week, during the summer months. - Familiarity with Python, AI/ML concepts, and/or .NET programming technologies. - Ability to organize and analyze data, explain technical results, and work effectively in a collaborative engineering environment. ## Preferred Qualifications: - Coursework, project, research, or internship experience involving vehicle dynamics, motorsports, controls, simulation, optimization, statistics, or data science. - Experience using Python libraries. - Familiarity with time-series data, regression, classification, clustering, anomaly detection, or probabilistic modeling. - Understanding of model explainability, uncertainty, data quality, and responsible use of generative AI tools in engineering work. - Ability to work with large datasets and communicate results through clear visualizations and concise technical documentation.