Lead Data Scientist — Human Movement & Sensor ML

Nike Inc; Beaverton (OR); Hybrid; USD 130,000 - 190,000; Full time

Job summary

Nike Sport Research Lab in Beaverton, Oregon seeks an experienced Lead Data Scientist to guide complex projects at the intersection of biomechanics and advanced analytics. You will lead analytical work, collaborate with researchers, and deliver credible, actionable insights about human movement and athletic performance.

The role emphasizes hands-on coding, rigorous experimentation, and clear communication of assumptions and limitations, with mentorship of junior scientists and close

Qualifications

• Master’s degree or higher in a related field (as listed).
• 6+ years of applied data science experience including ownership of complex projects.
• Strong Python proficiency and maintainable software development practices.
• Experience with complex measurement data (time-series, IMUs, wearable sensors, vision data).

Responsibilities

• Lead technical execution of complex projects using sensor and camera data to study movement and performance.
• Develop analytical workflows using IMU, wearable, and camera data.
• Connect model outputs to real-world movement phenomena, with explicit assumptions and limitations.
• Provide mentorship and code/analysis reviews to team members.
• Build reusable data and software pipelines for reproducible research.
• Evaluate emerging methods and translate advances into practical capabilities.

Skills

Python proficiency

Data science leadership

Machine learning

Computer vision

Time-series / sensor data analysis

Communication skills

Biomovement knowledge

Education

Master’s degree in Computer Science, Data Science, Statistics, Engineering, Biomechanics, Kinesiology, Applied Mathematics, Physics, or related field

Tools

Python

TensorFlow

PyTorch

Git

Job description

Nike Sport Research Lab in Beaverton, Oregon seeks an experienced Lead Data Scientist to guide complex projects at the intersection of biomechanics and advanced analytics. You will lead analytical work, collaborate with researchers, and deliver credible, actionable insights about human movement and athletic performance.

The role emphasizes hands-on coding, rigorous experimentation, and clear communication of assumptions and limitations, with mentorship of junior scientists and close