NIKE, Inc.チームの 一員になる
NIKE, Inc.の仕事は、世界トップクラスのアスリートたちにウェアやシューズを提供することだけではありません。ここは自分の潜在力を探求し、限界を取り払って、可能性を大きく広げることができる職場です。Nikeが求めているのは、意欲を持って成長し、自分の頭で考え、夢を思い描き、新しく創造できる人材。多様性を武器に創意工夫を奨励することで、企業文化を発展させています。Nikeブランドは、成功に向かって努力を続ける人や、チームを率いるリーダーや、大きな目標を思い描ける人材を求めています。常に進化し続ける仕事にはやりがいがあり、NIKE, Inc.では従業員一人ひとりが各々のスキルと情熱を日々の業務に注いでいます。
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.
* if you have body, you are an athlete
WHO YOU’LL WORK WITH
The Principal Data Scientist partners with research scientists in physiology, biomechanics, perception, and behavioral science, as well as other data scientists, engineers, product managers, designers, and solution architects. This role reports to the Director of Data Science and collaborates across dynamic, multi-functional teams to accelerate innovative product development. The team is recognized for its culture of curiosity, collaboration, and impact within Nike and the broader industry.
WHO WE ARE LOOKING FOR
Nike Sport Research Lab seeks a Principal Data Scientist who combines deep technical expertise with a passion for advancing human performance. The ideal candidate is a hands-on creative problem-solver, a collaborative leader, and a strategic thinker who thrives in multidisciplinary environments. This individual brings a proven track record of leveraging science and technology to drive innovation in sport science, product development, or related fields.
Required Qualifications:
PhD or Master’s in Statistics, Computer Science, Electrical/Biomedical engineering, Economics, or related field, Will accept any suitable combination of education, experience and training.
7-9+ years demonstrated experience in Data Science, including expertise in data synthesis, machine learning, statistical modeling, causal inference, or signal processing.
Demonstrated expertise with Python, and data analysis stacks (such as NumPy, SciPy, pandas, Spark, etc.)
Experience with AWS infrastructure, Spark, Databricks, and SQL.
Demonstrated practice of software engineering best practices within technical orgs (git for version control, structured code reviews, automated tests, CI/CD pipelines, and maintainable, reproducible build environments)
Proven ability to define, initiate, and supervise analytics and modeling efforts.
Strong track record of translating business needs into research requirements and strategy.
Ability to interpret and implement methods described in research papers and articles in signal processing, machine learning, deep learning, mathematical modeling, and related fields.
Excellent interpersonal and communication skills, with experience communicating technical information in both written and verbal formats.
Desired Qualifications:
Experience with experimental design and statistical inference, including adaptive experimentation, A/B testing, bandit optimization, and causal inference.
Proficiency in advanced machine learning methods, including classification, regression, deep learning, and computer vision algorithms.
Familiarity with time-series analysis, predictive modeling, and forecasting using large-scale, real-world datasets (e.g., sensor, image, or behavioral data).
Experience developing and deploying models that learn from expert input and emulate expert decision-making.
Understanding of, or working knowledge in, cardiovascular physiology, biomechanics, perception science, or related fields.
Experience with bio-signals, wearables, and inertial measurement technologies.
Peer-reviewed machine learning publications or other demonstrable contributions (e.g., GitHub, apps, products).
Experience leading or mentoring teams of data scientists and engineers in research or product settings.
Experience designing and delivering clear, impactful data visualizations for technical and non-technical audiences.
Experience building and maintaining robust data pipelines, ensuring data quality, integrity, and accessibility for analysis and modeling.
WHAT YOU’LL WORK ON
As Principal Data Scientist, you will play a pivotal role in advancing Nike’s sport science capabilities through innovative data science and machine intelligence. You’ll leverage your expertise to solve complex problems, drive impactful research, and deliver scalable solutions that power athlete and product innovation.
You will:
Apply expertise in signal processing, machine learning, sensor fusion, computer vision, and other areas of machine intelligence to solve complex problems using large, diverse datasets.
Develop and deploy predictive models in production environments to power personalized digital experiences for athletes and consumers.
Drive the development of large-scale experimentation capabilities and help identify causal factors influencing athletic performance and behavior.
Lead the creation, acquisition, and maintenance of high-quality datasets that enable ongoing exploration and unlock value for NSRL and partner organizations.
Investigate and evaluate new technologies, software, machine learning techniques, and capabilities to keep NSRL at the forefront of innovation.
Communicate technical information, methods, and findings clearly and concisely to technical and non-technical teams, partners, and senior management.
Create specifications and documentation for external professional services firms to achieve team objectives efficiently.
Stay connected with machine intelligence innovations across the industry and share insights with team members and partners throughout Nike.
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.
私たちの採用プロセス
01 応募
私たちのチームは、多様なスキルセット、知識、意見、アイデア、バックグラウンドを持つメンバーで構成されています。 職務内容、部門、チームを確認して、自分に合った役割を見つけましょう。
02 採用担当者に会う、または評価を受ける
コーポレートの職務を選んだ場合、面接プロセスを開始するために採用担当者が連絡を取り、面接が終了するまでの間、あなたの主な窓口となります。 リテール職の場合は、チャットとクイズを含む対話型の評価を行うことになります。所要時間は約10~20分です。 職務に関わらず、私たちは皆さんの人となりを知りたいと思っています。世界トップクラスのサービスに対する考え方や、あなたの独自性について遠慮なく話してください。
03 面接
Nikeについて調べ、Nikeが何を求めているのかを理解し、あなたの人となりや経歴について詳しく知るために設定された質問に答えられるよう準備し、自信を持ってこのステージに臨んでください。