Data Science Manager - Motorsports

Workplace Classification:

Hybrid: This position does not require an employee to be on-site full-time to perform most effectively. This position requires an employee to be onsite up to 3 times per week, with flexible schedule for periodic race weekend remote support.

GM Motorsports Software Engineering is looking to expand its motorsports data science and analytics group. GM Motorsports is currently racing in NASCAR, IndyCar, IMSA and is currently pursuing an entry into Formula 1.

The Team:
GM?s Motorsports Software team analyzes, defines, and delivers next generation groundbreaking Motorsports IT software solutions. Using both innovative cloud-based infrastructure and software development standards, these solutions enable innovative interactions between GM Global Engineering, GM Motorsports, and our Race teams that accelerate our drivers to the finish line first! Our combined team of analysts, architects, developers, data engineers, testers, and project managers work with GM Motorsports Engineering and Race teams to ensure podium wins for GM?s NASCAR, IndyCar, and IMSA sportscar teams!

The Role:

In this Data Science Manager role, you will have the opportunity to work hands-on with our product, full stack development and data engineering teams to develop solutions for strategic & analytic tools. As the Data Science Manager, you will be responsible for leading, mentoring, and developing a high-performing team of data scientists while ensuring alignment with GM?s strategic objectives. In addition to technical expertise, you will be expected to demonstrate exceptional leadership, communication, and problem-solving skills.

This is an opportunity to lead by example, cultivate a collaborative culture, and guide your team through complex, data-driven projects to deliver impactful results for our race teams. The team is responsible for both advanced analytics strategy and applied, project-based solutions, focusing on applying machine learning and artificial intelligence techniques to address specific needs of our internal software and engineering partners, and GM key partner race teams. Additionally, you will drive development activities in accordance with appropriate methodologies to deliver tactical and strategic value each week to make a podium difference.

Responsibilities Include
? Team Leadership & Development: Lead, mentor, and inspire a team of data scientists, fostering a culture of collaboration, continuous learning, and professional growth. Provide guidance and constructive feedback to help individuals thrive and reach their full potential.
? Strategic Vision & Solution Development: Drive the development of data-driven strategies and solutions that address complex business problems. Engage with key stakeholders across technical and non-technical teams to ensure alignment with business goals and prioritize initiatives that maximize impact.
? Collaboration & Cross-Functional Engagement: Cultivate strong relationships with cross-functional teams to ensure smooth execution of projects and the effective delivery of data solutions. Facilitate clear communication between technical teams and stakeholders, translating complex data insights into actionable recommendations.
? Innovation & Technical Leadership: Lead the application of advanced machine learning, AI, and predictive analytics techniques to drive race team performance. Encourage your team to experiment with new approaches, continuously improve existing models, and push the boundaries of what?s possible.
? Decision-Making & Problem Solving: Provide strategic direction in the development and optimization of predictive models, ensuring they meet race team needs and align with overall business objectives. Leverage your strong problem-solving abilities to navigate challenges and make informed, data-driven decisions.
? Data Visualization & Communication: Ensure that complex data insights are clearly communicated to both technical and non-technical stakeholders through effective data visualization techniques. Tailor your communication style to your audience, ensuring clarity, understanding, and buy-in.

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