Lead Data Scientist

Full time

Employment Information

Become a Part of the NIKE, Inc. Team

NIKE, Inc. does more than outfit the world’s best athletes. It is a place to explore potential, obliterate boundaries and push out the edges of what can be. The company looks for people who can grow, think, dream and create. Its culture thrives by embracing diversity and rewarding imagination. The brand seeks achievers, leaders and visionaries. At NIKE, Inc. it’s about each person bringing skills and passion to a challenging and constantly evolving game.

Open to remote work except in South Dakota, Vermont and West Virginia.

The annual base salary for this position ranges from $119,400.00 in our lowest geographic market to $267,500.00 in our highest geographic market. Actual salary will vary based on a candidate’s location, qualifications, skills and experience. Information about benefits can be found here.


We are looking for an experienced Lead Data Scientist to join Nike’s Insights, Data Science, and Analytics (IDSA) team. This role will be part of a multi-functional agile squad and will provide technical expertise and leadership in building predictive and prescriptive analytic solutions to support Nike’s supply and inventory planning strategies and optimization goals.

The candidate needs to be a diligent teammate with strong hands-on data science and analytics experience, drive, and curiosity. You know how to rise above the numbers and explain the crucial insights to users at all levels. You simplify and distill business complexity into testable hypotheses and scalable solutions. While you are proficient in a plethora of advanced modeling techniques, you are able to identify the technique optimal for the task at hand based on the business requirements, your knowledge of the data and the technique’s assumptions, interpretability and adaptability. You ask good questions, are continually learning as well as finding opportunities to share knowledge with others.


If this is you, you will be part of IDSA’s Supply & Inventory Planning (S&IP) Data Science squad. We deliver data science products and solutions to support Nike’s business strategies and initiatives spanning demand, supply, and inventory management.

You will have opportunities to influence product direction, guide standard methodologies in data science and engineering, and help deliver technical projects from inception to completion. Specifically, you will:

  • Work with the squad through assessment of business requirements, data constraints, and pros/cons of alternative analytics techniques to determine the best solution approach. Contribute to the planning, scheduling and value measurement of the work to meet timeline targets and success criteria.
  • Drive implementation, and maintenance of production-grade data science (statistical, mathematical, and AI/ML) and operation research models to determine optimal level of factory utilization, capacity, costs, lead times, and reduction of un-planned.
  • Help deliver improvement of aligning manufacturing capacity with demand by understanding product attributes, partner’s manufacturing capabilities and complexity.
  • Explore business drivers of cost, timely performance (of products and materials), root causes of quality issues, and strive to achieve Nike’s sustainability goals.
  • Help craft Nike’s analytical platforms and products by identifying foundational data science capabilities and creating reusable analytical components.
  • Support the adoption of analytic products through effective storytelling and collaboration with key partners.
  • Share knowledge with others on the team; continue to adapt or develop new methods and learn new software packages as available in the literature and recent publications.


You will work with the Director of Advanced Analytics and serve as a Lead Data Scientist in the GSM Advanced analytics squad, which includes other data scientists (and data engineer partners). You will collaborate across the broader organization with business teams in Global Sourcing & Manufacturing, Demand and Supply Management as well as other data, analytics and technology functions at Nike.


  • Advanced quantitative degree (Statistics, Mathematics, Operations Research, Computer Science or related field) and at least 5 years of related industry experience or Bachelor’s degree and 7-12 years related industry experience.
  • Deep knowledge of data science and optimization methodologies, including classical models, artificial intelligence and machine learning algorithms, and linear and non-linear optimization techniques.
  • Advanced skills in programming languages (particularly Python and SQL) and ability to apply them for data acquisition, preprocessing, modeling, and monitoring.
  • Familiarity with the wide range of data science/analytics software tools (e.g. Jupyter Notebook, SQL consoles, Hadoop, Spark) and cloud computing platforms (e.g. Amazon Web Services).
  • Experience in building, training, scoring, tuning and maintaining predictive models in production at enterprise scale and familiarity with mainstream packages relevant to leading all stages of Data Science/Analytics lifecycle.
  • Proven understanding of supply chain and inventory management
  • Familiarity with the Agile development process and demonstrable ability to prepare a project plan, communicate the plan to the team and break the work down to trackable tasks.

NIKE, Inc. is a growth company that looks for team members to grow with it. Nike offers a generous total rewards package, casual work environment, a diverse and inclusive culture, and an electric atmosphere for professional development. No matter the location, or the role, every Nike employee shares one galvanizing mission: To bring inspiration and innovation to every athlete* in the world.

NIKE, Inc. is committed to employing a diverse workforce. Qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, gender expression, veteran status, or disability.


Join our newsletter to get monthly updates on data science jobs.