Applied Scientist - Supply Chain

Build at Auger

• Clear ownership, not decision by consensus
• First principles over inherited patterns
• Shipping systems, not slide decks
• Fast feedback from reality, not opinions

• 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.
• Frame multi-objective optimizations balancing cost, service, and emissions; compute Pareto frontiers and quantify trade-offs.
• 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