Applied Scientist - Supply Chain
Listed on 2026-07-26
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IT/Tech
AI Engineer (Applied/Software), Data Scientist, Machine Learning/ ML Engineer
About the Team & Role
We are seeking Supply Chain Applied Scientists to join Russell Allgor's team in Bellevue, WA or Dallas, TX.
In this role, you will design, develop, and deploy advanced AI and optimization solutions to address some of the most pressing problems in modern supply chains — from network design and demand forecasting to inventory optimization and risk management.
This role requires deep technical expertise in data science, machine learning, and optimization, as well as the ability to lead cross-functional teams and influence senior executives. At times, you may be assigned to a specific customer engagement and operate in a customer-facing role translating a customers supply chain objectives into the science required to bring Auger's Autonomous Operating System to life in their ecosystem.
Key Responsibilities- Develop and implement novel models in optimization, machine learning, and AI tailored to large-scale supply chain problems.
- Translate complex scientific concepts into practical, scalable solutions that drive measurable business impact.
- Formulate and solve large-scale mixed-integer and stochastic programs (network design, facility location, inventory, routing) using decomposition (Benders/Lagrangian), cutting planes, and column generation.
- Build probabilistic demand/supply models (e.g., Bayesian hierarchical time series), deliver calibrated forecasts, and quantify uncertainty with prediction intervals/conformal methods.
- Collaborate closely with engineers, product managers, and customer teams to bring prototypes into production.
- Engage directly with enterprise executives, articulating the value of AI and data science solutions with confidence and clarity.
- Publish, present, and evangelize Auger’s thought leadership in supply chain science and AI.
- PhD in Mathematics, Operations Research, Computer Science, Industrial Engineering, or a related field.
- Demonstrated expertise in optimization, machine learning, or enterprise-scale data systems
. - Proven leadership experience scaling cross-functional data and AI teams.
- Deep technical credibility in AI and data science, with a track record of delivering applied solutions in industry.
- Exceptional EQ and collaboration skills
, with the ability to unify scientists, engineers, product leaders, and customers around a shared vision. - Experience in supply chain, logistics, or enterprise operations
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