We are a leading chemical company, with the best teams developing intelligent solutions for our customers, and for a sustainable future.
We connect and develop people with diverse talents all over the world. For you, this means a variety of ways to progress.
Not only your performance but also your personality matter to us, regardless of gender, age, ethnicity, orientation, and background. At BASF, careers develop from opportunities.
Objectives of the position
- 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).
