Senior Human Performance Researcher - Data Analysis

WHO YOU’LL WORK WITH 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. This role focuses on turning the data we collect, from in-person studies to large-scale field data, into clear answers. You will partner across the Lab and with digital technology, engineering, data science, service design, and innovation teams.

WHO WE ARE LOOKING FOR 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 and biomechanics with hands-on experience analyzing complex data sets, large and small, from motion capture, wearable sensors, surveys, and other field sources.

You are a creative and methodical problem solver who is comfortable with messy, real-world data, can manage multiple projects, works independently in ambiguity, and communicates complex findings clearly to technical and non-technical audiences.

WHAT YOU’LL WORK ON

You will analyze data across the research lifecycle, from focused in-person studies in the Lab and field to large-scale data sets from wearables, surveys, and digital platforms. You will help shape study and data designs, build processing and analysis pipelines, and support data collections as needed so you understand the data from the source.

You will build expertise in sensor data and analysis tools, translate research into actionable recommendations, and see how the Lab’s work serves athletes* and shapes the future of sport.

KEY RESPONSIBILITIES

• ·       Condition, process, and analyze biomechanical and human movement data from in-lab, on-field, and remote studies with athletes of different levels and backgrounds.
• ·       Analyze large-scale field data sets from wearables, surveys, and digital platforms, combining sources to answer priority research and product questions.
• ·       Build and maintain repeatable, well-documented data pipelines, quality checks, and analysis workflows in Python and Databricks.
• ·       Apply sound statistical methods to study design, analysis, and interpretation, including mixed, longitudinal, and repeated-measures data.
• ·       Interpret results and share credible, decision-ready insights through reports, dashboards, and visualizations for physical and digital product innovation.
• ·       Partner with data collection researchers on protocols and data standards, and support in-person collections as needed.
• ·       Share feedback to improve data quality, research processes, and athlete insight.
• ·       Apply foundations of computational biomechanics to analysis and interpretation of human movement data.

QUALIFICATIONS

• ·       Master’s degree in biomechanics, bioengineering, exercise science, kinesiology, or a related field.
• ·       3+ years of research experience analyzing human participant or athlete data from laboratory, field, or remote settings.
• ·       Deep knowledge of biomechanics, experimental design, statistical methods, and human movement data.
• ·       Experience working with data from 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.
• ·       Strong proficiency in Python and SQL for data processing and analysis. Experience with Databricks or similar large-scale data platforms strongly preferred; Visual3D, OpenSim, or musculoskeletal modeling a plus.
• ·       Experience cleaning, merging, and analyzing large, messy, multi-source data sets, including time-series sensor and survey data.
• ·       Experience communicating results through clear visualizations and dashboards.
• ·       Demonstrated curiosity, initiative, attention to detail, and comfort working independently in ambiguity.
• ·       Industry research and experience in running or lateral sports strongly preferred.
• ·       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.
• We offer a number of accommodations to complete our interview process including screen readers, sign language interpreters, accessible and single location for in-person interviews, closed captioning, and other reasonable modifications as needed. If you discover, as you navigate our application process, that you need assistance or an accommodation due to a disability, please complete the Candidate Accommodation Request Form .