Racing Tire Data Scientist — Motorsports Analytics

Paddock; Concord (NC); Ibrido; USD 130.000 - 180.000; Tempo pieno

Vantaggi offerti da questo lavoro

Hybrid work model

Relocation benefits

Descrizione del lavoro

General Motors, Concord, NC, is seeking an Electronics/Analytics role focusing on tire intelligence within Motorsports. The role develops data-driven insights from tire, vehicle, and race data to guide design decisions and event execution.

The position emphasizes building scalable analytics, dashboards, and repeatable workflows, with collaboration across Tire Science, data engineering, and performance teams. A strong background in data science and engineering leadership is essential.

Competenze

• Bachelor’s degree in a technical field; 5+ years data science in physical systems is expected.
• Experience building end-to-end data workflows for multi-source datasets.
• Ability to translate engineering questions into scalable analytics solutions.

Mansioni

• Build and maintain data workflows ingesting tire, vehicle, and race data.
• Develop models to predict tire behavior and event performance.
• Create dashboards and reports for test reviews and race preparation.
• Collaborate with Tire Science, data engineering, and performance teams.
• Mentor engineers in data-driven problem solving.

Conoscenze

Data science

Python

Time-series modeling

Statistical analysis

Stakeholder communication

Project leadership

Formazione

Bachelor's degree in a technical field

Master's/PhD preferred

Strumenti

Azure Databricks

SQL

Python libraries (pandas, scikit-learn)

Descrizione del lavoro

General Motors, Concord, NC, is seeking an Electronics/Analytics role focusing on tire intelligence within Motorsports. The role develops data-driven insights from tire, vehicle, and race data to guide design decisions and event execution.

The position emphasizes building scalable analytics, dashboards, and repeatable workflows, with collaboration across Tire Science, data engineering, and performance teams. A strong background in data science and engineering leadership is essential.