Drive continuous improvement across the Asia Pacific Regional Supply Chain for Agricultural Solutions by leveraging data analytics to identify inefficiencies and implement data-driven solutions.
This role also leads digitalization and automation efforts, including data extraction, dashboard development in Power BI, and predictive analytics enablement.
Main Tasks
Advanced Analytics & Modeling
Develop predictive models for demand forecasting, inventory optimization, and lead time prediction.
Apply machine learning techniques (e.g., anomaly detection, planning data analysis) to large datasets to solve supply chain challenges.
Data Engineering & Automation
Manage and transform large datasets from ERP and planning systems (e.g., SAP).
Build automated data pipelines using Python, SQL, or similar tools.
Decision Support & Scenario Planning
Create simulation and optimization tools to support strategic planning and what-if analysis.
Monitor and refine models to ensure optimal performance.
Digital Supply Chain Projects
Lead or co-lead digital transformation initiatives (e.g., control towers, predictive maintenance, AI in logistics).
Collaborate with IT and data teams to enhance infrastructure and modeling capabilities.
Requirements
Bachelor’s degree in Data Science, Computer Science, Operations Research, Industrial Engineering, Supply Chain, or related fields.
Minimum 3 years of experience in Supply Chain Analytics, Data Science, or quantitative modeling.
Proficient in Python or R; strong SQL skills.
Experience with cloud platforms (e.g., Snowflake, Azure, AWS) and machine learning libraries (e.g., scikit-learn, TensorFlow).
Familiarity with Supply Chain Planning and Execution Systems (e.g., SAP IBP, Kinaxis).