Senior Human Performance Researcher. - Data Collection

Nike • Beaverton, OR

10d

About The Position

The Nike Sport Research Lab (NSRL) is a multidisciplinary team of researchers, innovators, scientists, engineers, and data experts who lead with science to make athletes measurably better. Our insights and capabilities shape Nike products, services, and athlete experiences. This role sits on the Athlete Guidance team, which studies and serves athletes of all levels in the Lab and in the environments where they train, compete, and live. You will partner across the Lab and with digital technology, engineering, data science, service design, and innovation teams. We are looking for a passionate and versatile Senior Researcher to plan and execute applied, athlete-centric research focused on performance and protection in sport. The ideal candidate combines a strong foundation in human movement science with hands-on experience in biomechanics, in-person and field-based data collection, wearable sensors, data analysis, and athlete consultation. You are a creative and methodical problem solver who can manage multiple projects, work independently in ambiguity, and communicate complex findings clearly to technical and non-technical audiences. You will work across the research lifecycle, from study planning, protocol development, and recruiting through athlete interaction, data collection, data conditioning, analysis, interpretation, and reporting. You will also develop tools and methods (including hardware and software design, as needed) that improve data acquisition, research quality, and athlete insight. You will build expertise in sensor technologies and analysis tools, translate research into actionable recommendations, and see how the Lab’s work serves athletes and shapes the future of sport.

Requirements

• Master’s degree in biomechanics, bioengineering, exercise science, kinesiology, or a related field.
• 3+ years of research experience with human participants or athletes across laboratory, field, or remote settings.
• Deep knowledge of biomechanics, experimental design, statistical methods, and human movement data.
• Hands-on experience with human movement technologies, such as foot and body scanners, instrumented treadmills, pressure mapping, force plates, marker-based or markerless motion capture, inertial measurement units, electromyography, and other wearable sensors.
• Proficiency in Python or similar tools for data collection, processing, and analysis.
• Experience maintaining and troubleshooting research equipment, software, diagnostic tools, or electrical systems.
• Demonstrated curiosity, initiative, attention to detail, and comfort working independently in ambiguity.
• Strong project management skills and the ability to deliver high-quality work in a fast-paced, collaborative environment.
• Excellent verbal and written communication, including explaining complex topics to technical and non-technical audiences.

Nice To Haves

• Experience with Databricks, Visual3D, OpenSim, or musculoskeletal modeling strongly preferred.
• Industry research and experience in running or lateral sports strongly preferred.

Responsibilities

• Aid in the design, preparation and execution of biomechanical data collections in-lab, on field, and via remote studies with athletes of different levels and backgrounds.
• Own key elements of the research process, including protocols, recruiting, study administration, data collection, analysis, interpretation, and reporting.
• Be the primary researcher responsible for calibration, operation, synchronization, and troubleshooting of data collection equipment.
• Aid in the interpretation of results to produce and share credible, decision-ready insights for physical and digital product innovation.
• Aid in preventative maintenance and troubleshooting of software, research equipment, and diagnostic tools, including electrical systems.
• Observe, gather, and share feedback to improve research processes and athlete interactions.
• Apply foundations of computational biomechanics to analysis and interpretation of human movement data.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior