- Location
- INDIA TECHNOLOGY CENTER
- Workplace
- Remote
- Type
- Full-time
- Department
- IT
- Seniority
- Director
- Experience
- 5+ years
- Education
- PhD
- Closing date
- Today
- Source
- Workday
Description
Who You’ll Work With
The Data Science & Advanced Analytics team sits within Supply Chain & Planning Technology (SCPT) at NIKE, Inc., driving forecasting, optimization, and simulation solutions across Nike’s supply chain. Reporting to the Senior Director of Data Science, this role partners closely with product, engineering, and business stakeholders across SCPT sub-domains, while collaborating with the broader Data Science Center of Excellence to elevate discipline standards enterprise-wide.
Who We Are Looking For
We’re looking for an experienced people leader who can operate at scale across squads and products, enforce delivery discipline, and build high-performing data science talent. The ideal candidate combines deep technical expertise in forecasting, optimization, and simulation with a player-coach approach—coaching teams to excellence while stepping in hands-on when critical delivery decisions demand technical judgment. They bring a track record of delivering production-grade data science solutions and translating analytical work into measurable business impact within complex, cross-functional environments. This leader is equally strong at establishing data science best practices—model governance, reproducibility, accuracy measurement frameworks—and at influencing senior stakeholders across organizational boundaries. Strong engineering sensibility, familiarity with modern development workflows, and a drive to accelerate teams through AI-enabled tooling round out the profile.
Key Qualifications:
Bachelor’s degree or equivalent combination of education, experience, or training
Advanced degree (Master’s or PhD) preferred in Data Science, Operations Research, Statistics, Industrial Engineering, Computer Science, or a related quantitative field.
15+ years of progressive professional experience across technology, analytics, and leadership roles.
5-10+ years of experience in data science, advanced analytics, or decision science, including delivery of production-grade forecasting, optimization, and/or simulation solutions in complex operational domains.
Significant experience leading and developing data science teams, including managing senior individual contributors and/or managers, with demonstrated ability to drive performance, coaching, and organizational development at scale.
Hands-on experience delivering solutions using modern tooling (Python, SQL, cloud data platforms), with familiarity with engineering best practices (GitHub, PR workflows, code review discipline, CI/CD integration).
What You’ll Work On
As Director of Data Science & Advanced Analytics within SCPT, you’ll lead delivery and people leadership across data science teammates mapped to one or more SCPT sub-domains—driving forecasting, optimization, and simulation capabilities while ensuring your teams operate to the highest standards of quality, rigor, and impact.
Your responsibilities include:
Own delivery outcomes for data science teammates supporting products across your assigned SCPT sub-domain(s), ensuring delivery quality, operational stability, and the right balance between new capability development and sustained production performance.
Lead your team as a player-coach—driving performance management, coaching, feedback, and career development while maintaining a high delivery bar, and stepping in hands-on to unblock critical technical decisions.
Ensure solutions align with architectural and technical standards; guide critical design tradeoffs across modeling approach, production readiness, and delivery priorities, and anticipate cross-squad dependencies and technical risks.
Champion Data Science CoE standards adoption across forecasting strategy, accuracy measurement, optimization modeling rigor, and simulation validation—and provide leadership within the CoE to evolve discipline standards at scale.
Establish engineering excellence expectations across your teams—PR rigor, code quality, documentation, reproducibility—and partner with engineering leaders to align DS workflows with CI/CD and platform expectations.
Drive adoption of AI tooling (Copilot, Cursor) and delivery tooling (GitHub, Jira, Confluence) to improve speed, quality, and outcomes across your organization.
Translate complex analytical concepts into clear, decision-ready narratives; influence executive stakeholders and drive alignment on data-driven decisions across SCPT and beyond.
