# Senior Specialist I, Business Analytics at ASM

> Build demand forecasts and inventory models to keep critical spare parts available for customers while controlling cost.

- Company: ASM (asm.com)
- Location: Singapore
- Places: Singapore
- Posted: 2026-11-06
- Level: Senior
- Team: Business Analytics, Spares Supply Chain
- Apply: https://www.asm.com/open-vacancies/?gh_jid=5025254101
- Page: https://ye.saranatour.dev/jobs/senior-specialist-i-business-analytics-asm-kn7eyvbcmxqhwpapj3k2ezzn218hr96x

## The posting

Senior Specialist I, Business Analytics
ASM · Singapore

**Step into a career with ASM, where cutting edge technology meets collaborative culture.**​

For over 55 years ASM has been ahead of what’s next, at the forefront of innovation and what’s technologically possible. With more than 4,500 ASMers representing 70 nationalities, our people and our advanced semiconductor devices are playing a crucial role in trends such as 5G, cloud computing, AI, and autonomous driving. But we’re more than just a tech company. We value diversity, inclusion and sustainability as we strive to make a positive impact on the world. Our development programs help support your growth, shaping your future and pushing the boundaries of innovation to unleash potential.

**Job's mission**

As a Senior Specialist I, Business Analytics, you will turn complex supply-chain data into decisions that help ASM keep critical parts available for our customers while improving inventory, cost, and lead-time performance. You will own and develop forecasting, inventory, capacity, and optimization models, working across Spares Supply Chain, Operations, Procurement, Logistics, Service, Finance, and IT to solve real operational challenges. Your insights will go beyond reporting, translating data, business context, and scenario analysis into practical recommendations that strengthen customer service and supply-chain resilience.

**What you will be working on**

- Develop demand forecasts using historical demand, installed-base data, customer commitments, service requirements, equipment plans, consumption patterns, and other relevant business drivers.
- Apply statistical and machine-learning methods to intermittent, lumpy, seasonal, and rapidly changing demand across parts, product families, customers, regions, warehouses, and suppliers.
- Build expected, upside, downside, and constrained-demand scenarios, and evaluate forecast performance using measures such as WAPE, MAE, forecast bias, Forecast Value Added, and service-level outcomes.
- Translate forecasts into practical recommendations for purchasing, inventory, supplier capacity, and allocation decisions.
- Design inventory policies covering safety stock, reorder points, replenishment parameters, target stock levels, and order quantities to balance availability, working capital, obsolescence risk, and logistics cost.
- Segment inventory using dimensions such as ABC value, XYZ demand variability, criticality, lead time, lifecycle, and supply risk, identifying shortage risks as well as excess, obsolete, slow-moving, and single-source inventory.
- Analyze demand, backlog, material availability, and supplier and operational capacity to identify bottlenecks and anticipate risks to customer commitments.
- Develop allocation, load-balancing, inventory-rebalancing, and optimization models across suppliers, sites, warehouses, transportation routes, and operational resources.
- Run what-if scenarios for demand surges, supplier disruptions, shortages, capacity constraints, alternate sources, and expedited shipments, quantifying the service and financial impact of different decisions.
- Analyze end-to-end lead time and logistics cost, identifying opportunities in transportation, consolidation, inventory positioning, supplier performance, customs, receiving, inspection, and internal handling.
- Combine quantitative evidence with insights from planners, suppliers, customers, procurement, service teams, and subject-matter experts, clearly docum