Motorsports Sportscar Data Analyst

JR United Kingdom; Swindon; Hybrid; GBP 60,000 - 100,000; Full time

Job summary

An innovative firm is seeking a Motorsports Sportscar Data Analyst to leverage data science in developing race strategy tools. This role involves refining AI/ML models, creating tire degradation models, and collaborating with technical teams to enhance race strategy analytics. The successful candidate will work in a hybrid environment, balancing remote work with essential on-site collaboration. If you're passionate about motorsports and data-driven decision-making, this opportunity offers a dynamic and exciting career path.

Benefits

Relocation benefits

Flexible schedule

Travel opportunities

Qualifications

• 5+ years in top-level motorsports series with strategy tools experience.
• Deep knowledge of motorsports race strategy tools and analysis techniques.

Responsibilities

• Evolve existing AI/ML models and develop race strategy tools.
• Collaborate with technical teams to support race strategy analytics.

Skills

Python

AI/ML modeling techniques

Data analysis

Mathematics

Statistical analysis

Interpersonal skills

Education

Bachelor’s Degree in Engineering

Master’s degree in a quantitative field

Tools

MATLAB

Hadoop

Spark

SQL

NoSQL

Job description

Job Description

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 and real-time 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 Monte Carlo free-air simulations.
• Create tire degradation models, refining parameters and coefficient fits for accurate future predictions.
• Design and prototype visualizations to effectively convey insights, collaborating with IT and software teams for implementation.
• Use race strategy tools and standalone models to verify accuracy, understand performance, and identify areas for improvement. Collaborate with IMSA and WEC teams to implement these tools and derive insights for each race.
• Resolve true vehicle pace considering track migration, traffic, energy savings strategies, tire and fuel effects.
• Predict in-race and session-to-session pace variations to inform strategy and planning.
• Collaborate with technical teams across GM and motorsport divisions to develop and support race strategy tools and provide analytics guidance.
• Co-develop production race strategy software with data science and IT teams.
• Apply analysis techniques across different racing series to validate and refine models, transferring learning between series.

What You’ll Need (Required Qualifications)

• Bachelor’s Degree in Engineering, Physics, Mathematics, Statistics, Computer Science, Data Science, or related field.
• 5+ years in top-level motorsports series (NASCAR, IMSA, F1, IndyCar, WEC, etc.) with at least 2 years developing or using strategy tools during live races.
• Deep knowledge of motorsports race strategy tools and analysis techniques for live decision-making.
• Proficient in Python, MATLAB, or similar programming languages.
• Familiarity with AI/ML modeling techniques and their industry applications.
• Strong organizational skills, attention to detail, and forward-thinking mentality.
• Excellent interpersonal skills, with experience in cross-team collaboration and mentoring.
• This role may offer relocation benefits and requires up to 10% travel within the US.

Preferred Qualifications

• Master’s degree in a quantitative or related field.
• Knowledge of tire modeling, construction, testing, and validation.
• Experience with simulation workflows in professional motorsports and vehicle performance optimization tools.
• Experience with machine learning libraries and big data tools (Hadoop, Spark, SQL, NoSQL).