Establish a new data science capability within an existing supply chain-focused division to deliver measurable improvements in supply chain performance
Requirements
- Strong programming in Python (pandas, NumPy, scikit-learn, TensorFlow, PyTorch)
- SQL and data manipulation expertise
- Familiarity with BI tools (Power BI, Tableau, or similar)
- Experience with time series forecasting and demand planning algorithms
- Knowledge of supply chain concepts (inventory management, allocation, lead times)
- Experience with cloud platforms (AWS, Azure, or GCP) and MLOps practices
Responsibilities
- Develop AI/ML models: design, develop, and optimize machine learning (ML) and deep learning (DL) models for allocation, planning, forecasting, and inventory management
- Data processing: extract, clean, and preprocess large datasets from multiple supply chain systems for model training and evaluation
- Feature engineering: create and select meaningful features that improve model performance based on supply chain domain knowledge
- Model deployment: build scalable pipelines to deploy models into production, ensuring smooth integration with existing systems
- Performance monitoring: continuously monitor and tune models to maintain accuracy and adapt to changing business needs
- Automation: develop automated workflows for data ingestion, model retraining, and reporting
- Innovation: stay current with emerging AI/ML techniques and evaluate their application to supply chain challenges
Other
- 5+ years of data science or advanced analytics experience
- Strong analytical and communication skills
- Comfort working as a solo contributor, building solutions where no playbook yet exists
- Collaboration: partner with cross-functional teams (inventory, planning, merchandising, and engineering) to turn business requirements into technical solutions
- Problem solving: identify inefficiencies in supply chain processes and propose AI-driven improvements
