Description
NVIDIA is seeking a Principal Supply Chain Modeling Engineer to serve as a core technical architect and strategic partner to their Vice President. In this critical individual contributor role, you will personally own and compose highly complex mathematical models that dictate their global hardware procurement strategy.
Your models will directly simulate and forecast demand for fundamental technology elements, including semiconductor wafers, memory devices, substrates, and key sub-assemblies that require lengthy procurement periods. You will upgrade traditional simulations by building and deploying Machine Learning (ML) and AI models to predict supply anomalies, market disruptions, and non-linear demand shifts.
Responsibilities:
- Write, debug, and scale advanced simulation models in Python, MATLAB, and Excel from scratch.
- Build and deploy ML and AI models to predict supply anomalies, market disruptions, and non-linear demand shifts.
- Simulate multi-variable demand scenarios for silicon wafers, memory, substrates, and critical long-lead-time sub-assemblies.
- Translate complex algorithmic and AI-driven outputs into clear, actionable financial and operational recommendations for the VP.
- Audit massive datasets to ensure extreme precision, as your model outputs will directly commit millions of dollars in spend.
- Stress-test, refine, and modernize legacy planning sheets into automated, high-performance computing scripts.
- Partner closely with supply chain, procurement, finance, and engineering teams to evaluate scenario-based planning and long-range sourcing strategies.
Requirements:
- Bachelor's degree in Operations Research, Industrial Engineering, Computer Science, Data Science, Mathematics, Statistics, Physics, or an equivalent quantitative engineering discipline.
- Expert proficiency in Python (libraries like Pandas, NumPy, SciPy) and MATLAB.
- 15+ years of quantitative experience with a proven track record of building, running, and deploying complex mathematical, simulation, or financial models.
- 2+ years of hands-on experience designing, training, and deploying AI or algorithms based on learning from data.
- Ability to build complex, formula-dense spreadsheets, macro automation, and data models where rapid prototyping is required.
- Extreme detail orientation with demonstrated success in identifying edge-case anomalies in massive datasets.
- Demonstrated experience presenting raw data and model architectures directly to VP-level leadership.
Nice to Have:
- Advanced degree (Master's or PhD) with a focus on optimization, simulation, or machine learning.
- Prior background in the technology hardware, semiconductor, or electronics supply chain sectors.
- Familiarity with capacity planning, inventory theory, or procurement logistics.
- Experience deploying AI models into live cloud environments (e.g., AWS, Azure, GCP).
You will also be eligible for equity and benefits.