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Nike

Senior Data Scientist - Supply Chain Optimization, ITC

Posted 15 Days Ago
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Remote
Hiring Remotely in Karnataka, IND
Senior level
Remote
Hiring Remotely in Karnataka, IND
Senior level
Designs and productionizes optimization, forecasting, machine learning, and simulation models for global supply chain decisions. Builds end-to-end data pipelines, performs scenario and sensitivity analyses, and partners with supply chain, operations, product, engineering, and business stakeholders. The role supports demand planning, inventory optimization, sourcing, capacity planning, logistics, and fulfillment while contributing to model governance and mentoring junior data scientists.
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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. The team develops end-to-end digital transformation across global planning, inventory, logistics and supply chain operations. This team partners with supply chain, technology team, and product stakeholders across NIKE's India hub to deliver cutting-edge analytical and optimization solutions that shape how NIKE moves product around the world. This role reports to the Director of Data Science Supply Chain & Planning Technology and collaborates closely with global engineering, operations research, and business analytics teams, and with the broader Data Science Center of Excellence to elevate discipline standards enterprise-wide.

WHO WE ARE LOOKING FOR

We are looking for a Senior Data Scientist who combines deep expertise in optimization and operations research with strong machine learning fundamentals. The ideal candidate thrives at the intersection of data science and supply chain, has a track record of delivering production-grade models, and communicates complex quantitative results clearly to both technical and business audiences. You bring an ownership mindset, intellectual curiosity, and a passion for solving real-world supply chain problems at global scale.

  • Bachelor's or Master's degree in Data Science, Statistics, Operations Research, Industrial Engineering, Computer Science, or a related quantitative field.

  • 5+ years of professional experience as a data scientist or applied scientist.

  • Hands-on experience building optimization models using Python (Pyomo, PuLP, OR-Tools), commercial or open source solvers (Gurobi, CPLEX), or equivalent.

  • Hands-on experience building forecasting Model

  • Proficiency in Python and SQL, with experience in cloud or distributed data environments.

  • Strong experience with supply chain use cases: planning, inventory, logistics, e-com, manufacturing, or fulfillment are preferred.

WHAT YOU’LL WORK ON

As a Senior Data Scientist on the Supply Chain & Planning Technology team, you will design, build, and deploy advanced optimization and analytical models that power NIKE's global supply chain decisions — from demand planning and inventory positioning to sourcing and logistics. 

  • Design, develop, and productionize optimization models and forecast model to support supply chain decisions including demand planning, inventory optimization, sourcing, capacity planning, and logistics. 

  • Build and maintain end-to-end analytical pipelines covering data ingestion, feature engineering, model training, validation, and deployment. 

  • Apply statistical modeling, machine learning, and simulation techniques to complement optimization-based solutions. 

  • Partner closely with supply chain, operations, and product stakeholders across India and global teams to translate business problems into quantitative models and clearly communicate results and tradeoffs. 

  • Conduct model performance analysis, scenario testing, and sensitivity analysis to support decision-making under uncertainty. 

  • Contribute to best practices for model governance, reproducibility, documentation, and responsible use of data science solutions. 

  • Mentor junior data scientists through technical guidance and model reviews. 

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