At NASCAR, you will work alongside passionate people creating experiences fans feel and helping shape the future of sports and entertainment.
NASCAR is seeking a Junior Data Scientist based in Daytona Beach, Florida, to help transform data into actionable insights and intelligent solutions that drive business decisions across the organization. In this role, you'll analyze data, support predictive modeling initiatives, enhance AI-enabled analytics tools, and collaborate with stakeholders to solve real-world business challenges. This opportunity offers hands-on exposure to modern analytics, generative AI, and emerging technologies while helping shape the future of data-driven decision-making at NASCAR.
What You Will Do:
- Prepare, combine, and analyze data using SQL and Python, investigating data quality issues and documenting business definitions.
- Apply statistical methods and support predictive modeling to understand fan behavior, identify trends, forecast outcomes, and evaluate business performance.
- Help develop, maintain, and enhance AI-enabled analytics tools, including Python-based tools and MCP integrations.
- Test analytical tools and AI-generated answers against trusted SQL queries and reports; investigate errors and improve underlying logic, instructions, and tool descriptions.
- Collaborate with business partners to translate questions and feedback into analyses, visualizations, and practical tools, communicating findings and limitations clearly.
- Work with data engineering and business intelligence colleagues to create repeatable workflows, maintain documentation, and follow established data access and governance practices.
- Support user adoption, ongoing analytical needs, and additional projects as assigned..
- Up to 10% travel throughout race season.
What You Will Bring:
- Degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related field, or an equivalent combination of education and practical experience.
- Foundational SQL skills, including joins, aggregations, and common table expressions, and experience using Python for data preparation and analysis.
- Understanding of core statistical concepts and familiarity with basic machine learning methods and model evaluation.
- Foundational understanding of generative AI’s capabilities and limitations, an interest in learning MCP and tool calling, and a commitment to validating AI-generated results.
- Strong analytical, organizational, and communication skills, with attention to accuracy and the ability to explain technical findings in business terms.
- A collaborative, curious mindset and willingness to learn new tools, ask questions, and manage competing priorities.
Why This Role?
This is an opportunity to help shape how NASCAR leverages data, analytics, and emerging AI technologies to support business strategy and decision-making. You'll partner with teams across the organization to uncover insights, develop practical analytical solutions, and improve how employees access and interact with data. Whether you're building predictive models, validating AI-generated outputs, or helping create new analytics capabilities, you'll see your work make a visible impact while continuing to grow your expertise in analytics, machine learning, and generative AI.
Behind every race weekend are talented people helping shape the future of sports and entertainment. If you are ready to make an impact alongside passionate teammates, we encourage you to apply.
Explore this opportunity and apply at www.careers.nascar.com.
Our people are the key to our success. That is why we offer competitive compensation, a comprehensive benefits package focused on wellness, and opportunities to grow and develop both personally and professionally.
NASCAR is an Equal Opportunity Employer and is committed to conducting recruitment and hiring activities in a fair, ethical, and legally compliant manner. In support of this commitment, all employment decisions are based on job-related qualifications, skills, experience, and performance, and are made without discrimination based on any legally protected characteristic, including but not limited to race, ethnicity, gender, religion, sexual orientation or gender identity, national origin, age, military or veteran status, disability, or any other status protected by applicable federal, state, or local law, including socioeconomic, marital, parental, or caregiving status.
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