Motorsports Sportscar Data Analyst

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

Job summary

Join a forward-thinking company as a Motorsports Sportscar Data Analyst, where you'll leverage your expertise in data science to enhance race strategy tools. This hybrid role involves collaborating with top motorsports teams to develop innovative solutions, utilizing AI/ML models, and analyzing real-time data during live races. You'll be at the forefront of motorsports analytics, ensuring that strategies are informed by accurate predictions and insightful analysis. If you're passionate about motorsports and data-driven decision-making, this is an exciting opportunity to make a significant impact in the industry.

Benefits

Relocation benefits

Flexible schedule

Travel opportunities

Qualifications

• 5+ years in motorsports with strategy tools experience.
• Deep knowledge of race strategy analysis and AI/ML techniques.

Responsibilities

• Develop and refine race strategy tools using data science techniques.
• Collaborate with teams to implement and analyze race strategies.

Skills

Python

MATLAB

AI/ML modeling

Motorsports race strategy

Data analysis

Education

Bachelor’s Degree in Engineering

Master’s Degree in a quantitative field

Tools

Hadoop

Spark

SQL

NoSQL

Job description

Job Description

Hybrid: This role is categorized as hybrid. The successful candidate is expected to report to Concord, NC three times per week at minimum. Due to the need to support some live race events during weekends, the role requires 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 strategy adjustments during live race events.

What You’ll Do

1. Evolve existing AI/ML models for application in Sportscars, refining Python codebases and reimagining models as needed.
2. Develop platforms for running and analyzing Monte Carlo simulations.
3. Create tire degradation models, refining parameters for accurate predictions.
4. Design new visualizations to convey insights effectively, prototyping and collaborating with IT and software teams for implementation.
5. Use race strategy tools and models to verify accuracy, understand performance, and identify areas for enhancement. Collaborate with IMSA and WEC teams to implement tools for each race.
6. Resolve true vehicle pace considering track migration, traffic, energy strategies, tire and fuel effects.
7. Predict in-race and session-to-session pace variations to inform strategy decisions.
8. Collaborate with GM motorsports teams to develop and support race strategy tools and provide analytical guidance.
9. Co-develop production race strategy software with data science and IT teams.
10. Apply analysis techniques across different racing series for process validation and model refinement.
11. Transfer learning approaches between series in which GM teams compete.

What You’ll Need (Required Qualifications)

• Bachelor’s Degree in Engineering, Physics, Mathematics, Statistics, Computer Science, Data Science, or related field.
• 5+ years of experience in top-level motorsports series (NASCAR, IMSA, F1, IndyCar, WEC, etc.), with at least 2 years developing or using strategy tools in such series.
• Deep knowledge of motorsports race strategy tools and analysis for live race decisions.
• Proficiency in Python, MATLAB, or similar programming languages.
• Familiarity with AI/ML modeling techniques and industry applications.
• Strong organizational skills, forward-thinking, and attention to detail.
• Excellent interpersonal skills, with experience in team relationships and navigating organizational politics. Patience and mentorship qualities are valued.
• This role may offer relocation benefits.
• Ability to travel within the US up to 10% of the time.

Preferred Qualifications

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