Lead Data Scientist, Innovation

The Nike Sport Research Lab (NSRL) is a multidisciplinary team of researchers, innovators, and scientists who lead with science to make athletes* measurably better. We deliver validated insights and innovative capabilities to drive the future of Nike products and services. The Data Science team in the NSRL unearths insights and automates recommendations to help everyday athletes* move better, while also supporting our product innovation teams!

Who we are Looking For

We are looking for an outstanding Lead Data Scientist to create capabilities and provide insights that enhance athlete performance, drive product innovation, and elevate consumer experiences, working primarily within our Field Research and Athlete* Services teams in the NSRL. In this role, you will transform raw athlete data -- collected in the lab and gathered in the real world using wearable devices and IoT sensors -- into meaningful insights and data products.

Key Responsibilities

• Develop and implement innovative ways of annotating and analyzing athlete* data to improve performance, prevent injury, and encourage continued engagement with Nike.

• Collaborate with sports scientists, researchers, and product designers to translate insights into actionable feedback for the development of future footwear and apparel products.

• Build and maintain robust data pipelines that ensure high-quality, relevant data collection and storage, facilitating efficient data analysis and model development.

• Communicate findings and insights to broad audiences to influence decision-making and strategy.

Qualifications

• Advanced quantitative degree (Statistics, Mathematics, Computer Science, Quantitative Social Science, Engineering, Physics or related field)

• 2 -4 years of industry experience as a data scientist or machine learning engineer

• Proficiency in common coding languages (Python, SQL, R)

• Experience working with sports-science time-series sensor data (biomechanical, physiological, and performance).

• Experience in machine learning, statistical modeling, and algorithm development

• Experience working with Amazon Web Services

• Demonstrated expertise in using Tableau for insight sharing to broad audiences.

• Proven track record of working cross-functionally and critically evaluating complex data from multiple perspectives, including questioning assumptions and validity.

• Excellent written and verbal communication skills, including ability to develop and deliver presentations.

• Passion for sports and a deep understanding of the athletic performance ecosystem.

• Comfortable owning projects end-to-end, including data ingestion, preprocessing, and cleaning, to developing, deploying predictive models, and extracting actionable insights.