Motorsports Tire Intelligence Scientist

Descripción

At GM Motorsports, we are driven by a clear purpose: to accelerate our teams’ ability to win on the racetrack and in the marketplace. Our vision is to be the benchmark of global motorsports excellence, inspiring enduring passion for our brands and products through world-class performance, innovation, and teamwork. We are looking for people who share our mindset and core values — ownership in organizational success, a commitment to add value to our team, and the courage to reject mediocrity in pursuit of exceptional results.

The Role

The Motorsports Tire Intelligence Scientist develops data and analytics solutions that turn tire, vehicle, testing, simulation, and race data into actionable engineering insight. This individual contributor partners with Tire Science, data engineering, data science, vehicle dynamics, data platform teams, and motorsports stakeholders to improve tire design decisions, operating window understanding, and event execution.

The role leads technically complex assignments, influences across functions through expertise and execution, and builds repeatable tools and workflows that support engineering decisions before, during, and after race events. At GM Motorsports, we are driven by a clear purpose: to accelerate our teams’ ability to win on the racetrack and in the marketplace. Our vision is to be the benchmark of global motorsports excellence, inspiring enduring passion for our brands and products through world-class performance, innovation, and teamwork. We are looking for people who share our mindset and core values — ownership in organizational success, a commitment to add value to our team, and the courage to reject mediocrity in pursuit of exceptional results.

What You’ll Do

• Build and maintain reliable data workflows that ingest, clean, align, and validate tire data from laboratory, rig, cleat, simulation, track, telemetry, and post-event sources.

• Combine structured and unstructured engineering data into analysis-ready datasets for tire performance studies and model development.

• Partner with information technology, software, and data platform teams to support data architecture, access, governance, traceability, quality, and documentation.

• Develop and apply statistical, artificial intelligence, and machine learning models to predict tire behavior, including grip evolution, wear, degradation, durability, warm-up behavior, rolling resistance, and event performance.

• Apply time-series analysis, feature engineering, uncertainty quantification, and interpretable modeling to noisy, sparse, and variable motorsports data.

• Work with Tire Science, data engineering, data science, vehicle dynamics, and performance teams to translate engineering questions into scalable analytical solutions.

• Analyze tire operating windows, pressure and setup sensitivity, degradation trends, and the tire contribution to lap time, stint length, and strategy outcomes.

• Deliver dashboards, notebooks, automated reports, and decision-support tools for test reviews, event preparation, race support, post-event assessments, and trend tracking.

• Standardize common analyses and create user-friendly workflows that reduce manual data handling and accelerate insight generation for trackside and remote teams.

• Collaborate with tire suppliers, motorsports partners, and internal stakeholders on technical data interfaces, standards, test methods, performance trends, and operating recommendations.

• Lead project scoping, analytical method selection, stakeholder alignment, and delivery planning for high-value analytics efforts.

• Mentor engineers and analysts in data-driven problem solving, model interpretation, reproducible workflows, and engineering communication.

• Establish best practices for coding, model validation, reproducibility, and technical communication.

What You’ll Need (Required Qualifications)

• Bachelor’s degree in data science, statistics, computer science, mechanical engineering, automotive engineering, applied mathematics, or a related technical field.

• 5 or more years of postgraduate experience applying data science, advanced analytics, or machine learning to physical systems such as tires, vehicles, chassis, durability, noise, vibration and harshness , or similar domains.

• Experience building analytical models in Python, or similar programming environments using modern data science libraries.

• Experience working with complex, multi-source engineering datasets and designing reliable end-to-end data workflows.

• Strong communication skills, with the ability to explain technical findings clearly to engineering and non-data audiences.

• Demonstrated technical leadership in project delivery, stakeholder alignment, and implementation of impactful analytics solutions.

What Will Give you a Competitive Edge (Preferred Qualifications)

• Master’s degree or doctorate in a relevant discipline.

• Experience with tire mechanics, tire performance, vehicle dynamics, or motorsports engineering.

• Experience analyzing time-series telemetry across testing, simulation, and race events.

• Experience with cloud-based data platforms such as Azure or Databricks.

• Experience building dashboards or decision-support tools for engineering users.

• Familiarity with GM engineering processes, motorsports program execution , or series-level technical requirements and regulations.

Success in This Role

• Faster, higher-quality tire performance analysis across testing, driver-in-the-loop simulation, and race events.

• Reusable and robust data pipelines, analytical workflows, and predictive models.

• Greater confidence in insights used for tire design, setup, and race-support decisions.

• Broader adoption of standardized analytics tools by Tire Science and race engineering teams.

• Practical, trusted use of artificial intelligence and machine learning to improve engineering decisions.

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Este puesto se clasifica como híbrido. Esto significa que se espera que el candidato seleccionado se presente en una ubicación específica al menos 3 veces por semana {o con otra frecuencia indicada por su líder}.

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