Supply Chain Analytics Center of Excellence (ACOE) team at Western Digital Corporation improves the supply chain performance by using data science and advanced analytics. As part of the Supply Chain Innovations group, ACOE develops, implements, and deploys quantitative models to optimize all aspects of the WDC supply chain, including but not limited to capacity planning, supply planning, demand planning, factory scheduling, and pricing.The past focus of ACOE is on predictive and prescriptive analytics. The models developed are then implemented and deployed in an ongoing basis at WDC, contributing substantial benefits to the company, either in the form of monetary savings or productivity enhancement. The future focus of ACOE is on cognitive analytics. This is to deploy machine learning algorithms on the big data platform at WD to predict customer ordering behavior and market dynamic behavior, so that the company can take proactive actions to match supply with demand. This is in line with the digital supply chain initiative ongoing at Western Digital—that is, incorporating outside-in data from customer value chain to our supply chain analytics, towards the end goal of positioning products when and where customer needs it, before even requested by customer. A few examples of the models developed by ACOE include:Insource versus outsource manufacturing split optimization: optimizes for the best split between insource and outsource manufacturing capacityPrice prediction: forecast market price using multiple regression on internal and external demand signals and market momentum factorsFactory scheduling: develops optimization engine to schedule which machine to work on which product in the factory production floor to minimizing delay, cycle time, and changeoversFactory simulation: develop simulation model for the factory to optimize for capacity buffer and inventory buffer to keep for each equipment
ESSENTIAL DUTIES AND RESPONSIBILITIES:
- Conduct quantitative modeling to provide solutions to new business problems.
- Deploy and improve optimization and/or simulation models owned by ACOE.
- Work with cross-functional teams to gather business requirements, implement model recommendations, and drive change management.
- Synthesize and present findings to all levels of management.
Education: PhD in Operations Research, Industrial Engineering, Statistics, Economics, Operations Management, or a quantitative field (such as Electrical Engineering and Mechanical Engineering).
Or, MS in a related field with quantitative research experience. Mastery of at least one programming language (Matlab, C, Java, or similar)
Proven programming skills to implement models from scratch (in Matlab, C, Java, or similar)Proven knowledge of mathematical optimization (Linear/Non-Linear/Mixed-Integer Programming and solution techniques) Deep understanding of basic statistical concepts and principles, such as regression and hypothesis testing, and simulation techniques, such as Monte-Carlo methodsGood understanding of machine learning algorithms, including a broad array of supervised learning, unsupervised learning, and reinforcement learning techniques. Experience with implementing scalable machine learning models on big data platforms.
SKILLS: Hands-on experience with statistical software (SAS, R, or similar)Experience with object-oriented programming (Python, C++, Java, etc.) is a plusProven ability to develop analytical models to solve business problemsKnowledge of supply chain management conceptsAbility to communicate effectively with cross-functional teamsAbility to both collaborate with cross-functional teams, as well as to work independently with minimal supervision