Collaborate with supply chain leadership to identify high-impact analytics use cases
Design, prototype, and implement machine learning and statistical models to address business challenges such as demand forecasting, inventory optimization, transportation efficiency, and supplier performance
Partner with data engineers to build scalable data pipelines and ensure clean, reliable data sources
Extract, clean, and transform large volumes of structured and unstructured supply chain data
Build dashboards and tools to visualize insights and track KPIs
Communicate findings clearly to both technical and non-technical stakeholders to drive data-driven decisions
Work closely with operations, planning, and procurement teams to understand domain-specific challenges and opportunities
Provide analytical support for key strategic initiatives and process improvements
Stay up to date with industry trends, tools, and best practices in AI, machine learning, and supply chain analytics.

Bachelor’s or Master’s degree in Data Science, Computer Science, Industrial Engineering, Supply Chain Management, or a related field
2+ years of hands-on experience in data science or advanced analytics, preferably within supply chain or operations
Strong programming skills in Python or R
Proficiency in SQL and experience working with large-scale databases
Experience with machine learning libraries (e.g., scikit-learn, XGBoost, TensorFlow)
Strong analytical, problem-solving, and critical thinking skills.
Preferred: Experience with supply chain systems (e.g., ERP, WMS, TMS)
Familiarity with tools like Power BI, Tableau, or similar for data visualization
Knowledge of optimization techniques and tools (e.g., linear programming)
Experience working in a manufacturing, retail, or logistics environment.

Data Scientist

Key skills