AI Scientist - Planning, Supply Chain Management

About the Role

As an experienced AI Scientist – Planning, you will design and develop the AI and optimization models that power Avathon's planning intelligence - demand forecasting, supply planning, inventory optimization, and S&OP decision support for customers across energy, mining, manufacturing, and logistics.

This role sits at the intersection of AI, ML and operations research. You will build models that work with complex supply chain data - demand history, ERP/MRP transactions, and commercial forecasts across multi-echelon networks with long lead times and constrained capacity. The work is equal parts applied research and production delivery. You will develop novel approaches where standard methods fall short and ship them into a platform used by enterprise customers. You will report into the Data Science org and work closely with product and engineering.

You Will

• Build demand forecasting models across industrial verticals, applying probabilistic, hierarchical, and intermittent demand methods where history is short or volatile
• Design supply planning and inventory optimization models across multi-echelon networks with capacity constraints and variable lead times
• Formulate and solve optimization problems (MIP, LP, constraint programming) for production scheduling, allocation, and resource planning
• Build simulation and scenario analysis frameworks to support S&OP and integrated business planning workflows
• Define evaluation metrics, build backtesting pipelines, and run controlled experiments to measure and improve model performance
• Integrate cross-domain signals from Avathon's Computational Knowledge Graph -- asset health, logistics, procurement - into planning models
• Own the path from research to production in collaboration with ML Engineering, delivering scalable and monitored services
• Mentor junior data scientists on technical depth and OR/ML fundamentals

You'll Have

• Ph.D. or master’s degree in operations research, Industrial Engineering, Statistics, Computer Science, Applied Mathematics, or a related quantitative field
• 6+ years of industry experience in applied ML, optimization, or Supply Chain planning systems
• Deep experience in at least two of: demand forecasting, supply/inventory optimization, production scheduling, or S&OP analytics
• Proficiency in Python with hands-on experience in optimization solvers (Gurobi, CPLEX, OR-Tools, or similar) or forecasting libraries (Prophet, statsmodels, GluonTS, or similar)
• Strong foundation in statistical modeling with sound judgment on when simple methods outperform complex ones
• Experience with supply chain and operational data - demand history, ERP/MRP transactions, and planning system outputs
• Ability to translate business problems into mathematical optimization or ML formulations
• Experience deploying models into production environments

Preferred Qualifications

• Ph.D. in Operations Research, Industrial Engineering, Statistics, or a related field
• Background in supply chain planning platforms or industrial AI (O9, Blue Yonder, Kinaxis, or similar), preferably within the supply chain industry
• Experience in supply chain planning platforms or industrial AI (O9 Solutions, Blue Yonder, Kinaxis, or similar) preferably from Supply Chain industry.
• Experience with multi-echelon inventory optimization or network design
• Familiarity with probabilistic programming or Bayesian methods for demand sensing
• Experience with cloud ML infrastructure (AWS SageMaker, GCP Vertex, or equivalent)
• Domain experience in energy, mining, manufacturing, aerospace, or logistics or Track record of publishing or presenting applied OR/ML work as plus