Senior Data Scientist - Supply Chain Optimization, ITC
NIKE, Inc. (company site, opens in a new tab)5+ yrsKarnatakaRemoteDirect career pageEst. 20–38 LPA
Posted 15h ago
Reach people at NIKE, Inc.
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at NIKE, Inc. you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design, develop, and deploy advanced optimization and forecasting models to support global supply chain decisions including demand planning, inventory optimization, sourcing, and logistics.
- Build and maintain end-to-end analytical pipelines for data ingestion, feature engineering, model training, validation, and deployment.
- Collaborate with global and India-based supply chain, operations, and product stakeholders to translate business problems into quantitative models and clearly communicate results including scenario and sensitivity analyses.
Minimum Requirements
- Bachelor's or Master's degree in Data Science, Statistics, Operations Research, Industrial Engineering, Computer Science, or related quantitative field.
- 5+ years of professional experience as a data scientist or applied scientist.
- Hands-on experience with optimization modeling tools in Python (e.g., Pyomo, PuLP, OR-Tools) and solvers like Gurobi or CPLEX.
- Proficiency in Python and SQL; experience in cloud or distributed data environments; strong experience with supply chain use cases (planning, inventory, logistics, e-commerce, manufacturing, or fulfillment).
Ideal Candidate Profile
- Expertise at the intersection of optimization, operations research, and machine learning applied to complex supply chain problems at global scale.
- Experience delivering production-grade models and leading end-to-end model pipelines addressing demand planning, inventory, sourcing, and logistics.
- Ability to translate complex quantitative results clearly to both technical and business audiences and provide technical mentorship to junior data scientists.