Job Description
This role is responsible for predicting and planning material consumption across The FAB Operations using advanced analytics and AI-driven models.
Ensures uninterrupted manufacturing and research activities by translating tool utilization, process flows, and roadmap changes into accurate material demand forecasts and actionable planning insights.
Key Responsibilities
Fab SVP & R&D Material Forecasting Systems & Continuous Improvement
- Develop consumption forecasts for semiconductor materials including chemicals, wafers, consumables, and spare parts.
- Build rolling forecasts (weekly / monthly / quarterly / annual) aligned with FAB SVP and R&D capacity.
- Improve and enhance available in-line systems with AI models
- Drive continuous improvement initiatives in FAB material planning and analytics maturity
- Analyze historical material usage and identify key drivers of consumption variability in R&D vs SVP environment
- Highlight risks related to supply disruption, long lead-time materials, and single-source dependencies
- Recommend inventory buffers, safety stock, and mitigation actions based on AI projections
AI-Driven Analytics & Modelling
- Apply AI techniques (time-series forecasting, regression, anomaly detection) to model material usage
- Use AI to detect abnormal consumption patterns (leaks, over-use, drift, process excursions)
- Automate forecasting models to reduce manual planning dependency and improve overall responsiveness
Cross-Functional Collaboration
- Work closely with Process Integration, Equipment Engineering, Fab Operations, Procurement, and Supply Chain
- Align forecasts with process qualifications, DOE runs, engineering lots, and technology transfers
- Support management and technical reviews with data-backed forecasts and clear assumptions
- Act as a bridge between technical teams and planning / procurement functions
- Provide Backup purchase enablers and able to multi-tasks as and when needed.
Requirements / Qualifications
- Bachelor's degree in Engineering (Chemical, Electrical, Materials, Industrial), Data Analytics, or related field
- Strong understanding of semiconductor fab or R&D operations
- Proven experience in material planning, consumption analysis, or process-linked forecasting
- Proficiency in data analytics tools (Excel advanced, Python, SQL, Power BI / Tableau)
- Ability to analyze complex datasets and translate them into operational decision.
Key Competencies
- Strong systems-thinking and forward-planning mindset
- High attention to detail with strong data governance discipline
- Ability to work under ambiguity, especially in R&D environments
- Confident communicator with both engineers and management
