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Director, Data Science - Global Supply Chain Analytics - Starbucks
Data Scientist
Lead the strategy, development, and deployment of advanced analytics for global supply chain operations, driving data‑driven decisions across sourcing, inventory, and logistics using Python, ML, and cloud technologies.
About the role
Key Responsibilities
- Define and execute the data science roadmap for global supply chain analytics, aligning with business objectives and stakeholder needs.
- Lead a high‑performing team of data scientists and engineers to build predictive models, optimization algorithms, and real‑time dashboards.
- Collaborate with cross‑functional partners in sourcing, logistics, and finance to translate complex business problems into analytical solutions.
- Oversee end‑to‑end data pipelines, ensuring data quality, governance, and scalability on AWS.
- Communicate insights and recommendations to senior leadership, influencing strategic decisions and operational improvements.
Requirements
- 10+ years of experience in data science or analytics, with at least 5 years in a leadership role within supply chain or operations.
- Proficiency in Python, SQL, and machine learning frameworks (scikit‑learn, TensorFlow, PyTorch).
- Hands‑on experience building and deploying models at scale on AWS (SageMaker, Redshift, Glue).
- Strong background in supply chain analytics, demand forecasting, inventory optimization, or related domains.
- Excellent communication skills and a proven ability to translate technical findings into actionable business insights.
Skills
pythonmachine learningsqlaws