Senior Data Scientist

This role sits within Nike's Data Science & Advanced Analytics team, which is part of Supply Chain and Planning Technology (SCPT) and works in the Sourcing, Supply, and Manufacturing (SSM) squad. The role is part of a cross-functional Agile squad and provides technical expertise and leadership in building predictive and prescriptive analytical solutions for Nike's global supply chain and operations, specifically in manufacturing, materials sourcing, and supply planning.

The role reports to the Director of Data Science and collaborates with data science leads, data and software engineers, product owners and managers, and business end users to deliver analytical and optimisation solutions.

• Design, develop, and product ionise optimisation and analytical models to support supply chain decisions, applying statistical modelling and simulation techniques and conducting model performance, scenario, and sensitivity analysis.
• Build and maintain end-to-end analytical pipelines covering data ingestion, feature engineering, model training, validation, and deployment.
• Work with the squad and global supply chain and operations partners to assess business requirements, data constraints, and trade-offs of alternative modelling techniques, contributing to planning, scheduling, and value measurement to meet timeline targets and success criteria.
• Explore business drivers of cost, on-time performance of products and materials, and root causes of quality issues, while striving to achieve Nike's sustainability goals.
• Help shape Nike's analytical platforms and products by identifying foundational data science capabilities and creating reusable analytical components.
• Support the adoption of analytical products through effective storytelling and collaboration with key partners.
• Share knowledge with the wider team and contribute to best practices for model governance, reproducibility, and responsible use of data science solutions.
• Influence product direction, guide standard methodologies in data science and engineering, and help deliver technical projects from inception to completion.

• Advanced quantitative degree in Statistics, Mathematics, Operations Research, Computer Science or a related field and at least 5 years of related industry experience as a data scientist or applied scientist, or a Bachelor's degree and 7-12 years of related work experience
• Any suitable combination of education, experience or training is accepted.
• Dependable teammate with drive, curiosity, strong hands-on data science and analytics experience including forecasting, optimisation, and simulation, and a deep understanding of supply chain and operations.
• Ability to rise above the numbers and explain complex insights to users at all levels, and to simplify and distil business complexity into testable hypotheses and scalable solutions.
• Proficiency in various advanced modelling techniques, with the ability to identify the optimal technique based on business requirements, available data, and the technique's assumptions, interpretability, robustness, and limitations.
• Consulting mindset; asks good questions, continually learns and keeps up with state-of-the-art developments, and finds opportunities to share knowledge with others.
• Deep knowledge of and hands-on ability in data science and optimisation methodologies, including classical models, artificial intelligence and machine learning algorithms, and linear and non-linear optimisation techniques
• Hands-on experience building optimisation models using Python and commercial solvers such as Gurobi, CPLEX, or equivalent.
• Advanced skills in programming languages, particularly Python and SQL, applied to data acquisition, preprocessing,…