Nike Sport Research Lab (NSRL) is looking for a Senior Data Scientist to analyze athlete data to make athletes measurably better, driving innovation in footwear, apparel, and athlete services.
Requirements
- Strong proficiency in Python, including expertise with core data science libraries such as pandas, NumPy, and scikit-learn.
- Proficiency in R or similar languages are also highly valued.
- Demonstrated experience in applying software engineering best practices to data science projects, including developing and maintaining robust, quality code, utilizing version control tools like Git, and collaborating within a modern software development life cycle.
- Strong foundation in statistical modeling, machine learning, and data visualization.
- Experience working with biomechanical, physiological, or performance data strongly preferred.
- Ability to manage large, diverse datasets and apply advanced analytical techniques.
Responsibilities
- Analyze and connect diverse datasets (biomechanical, physiological, sensor, product, consumer).
- Run advanced statistical analyses and machine learning models to uncover patterns and insights.
- Translate findings into actionable recommendations for product design, athlete services, and business partners.
- Collaborate with sports scientists, researchers, and engineers to design experiments and validate results.
- Partner with product innovation teams to embed data insights into next-generation footwear and apparel.
- Help build scalable pipelines, tools, and visualizations to make athlete data accessible.
- Contribute to developing common data taxonomies and standards across NSRL.
Other
- Masters/PhD degree in Data Science, Statistics, Computer Science, Sports Science, Engineering or related field or equivalent combination of education and experience
- 3+ years of experience in data science, analytics, or applied research (internships and academic research experience considered).
- Curious, analytical, creative — you thrive on solving complex problems with data.
- Passionate about sport, human movement, and applying science to real-world performance.
- Comfortable working across disciplines — from researchers and designers to engineers and business leaders.
