Applied Scientist II, SCOT-Optimal Sourcing Systems, Buying Science Team

What you'll do

• Set scientific strategy, decompose research problems, and develop team roadmaps.
• Design, code, and deploy novel optimization and machine learning solutions; build reusable science components and set technical standards.
• Influence cross-functional strategy, align stakeholders, collaborate across teams, and mentor others.

What they ask for

• PhD in operations research, applied mathematics, theoretical computer science, or equivalent; or a master's degree and 4+ years of experience in machine learning, statistical modeling, data mining, and analytics techniques.
• Knowledge of supply chain management concepts such as forecasting, planning, sourcing, optimization, and logistics, or equivalent.
• Experience building and deploying machine learning or optimization models for business applications at scale.
• Proficiency in Python and production-quality scientific software; technical depth in at least one of mathematical optimization, causal inference, sequential decision-making (RL/MDP), or stochastic modeling.

Nice to have

• Publication record in operations research, machine learning, or a related quantitative field.
• Experience with optimization solvers, reinforcement learning frameworks, deep learning frameworks, or designing and analyzing experiments in operational or supply chain settings.

Pay

USD 142,800.00 - 193,200.00 annually (base salary)

Tools

Python, Gurobi, OR-Tools, RLlib, Stable Baselines, PyTorch, TensorFlow

AI focus

Applies machine learning, deep learning, optimization, causal inference, and sequential decision-making to sourcing, vendor behavior, and supply chain problems; develops and deploys models in production.