Optimization Scientist - Route & Inventory Optimization (OR & RL)

As an Optimization Scientist specializing in Route & Inventory Optimization at a leading AI-driven supply chain solutions company, your role will involve supporting the development of intelligent optimization systems for route planning and inventory allocation. You will work alongside experienced scientists and engineers to tackle real-world logistics challenges using machine learning, reinforcement learning, and operations research techniques. Key Responsibilities: - Assist in Route Optimization Projects: - Support in modeling and solving simplified versions of Vehicle Routing Problems (VRP) under guidance. - Utilize Python libraries like Pyomo or OR-Tools to prototype optimization solutions. - Explore reinforcement learning methods (e.g., DQN, PPO) for dynamic routing decisions under uncertainty. - Support Inventory Optimization Efforts: - Learn to model multi-echelon inventory systems using basic OR and simulation techniques. - Analyze historical data to understand stock levels, service times, and demand variability. - Help design experiments to evaluate replenishment strategies and stocking policies. - Contribute to AI-Driven Decision Systems: - Assist in integrating ML forecasting models with optimization pipelines. - Participate in the development or testing of simulation environments for training RL agents. - Collaborate with the team to evaluate model performance using historical or synthetic datasets. Qualifications Required: - Currently pursuing or recently completed a degree in Computer Science, Data Science, Operations Research, Industrial Engineering, or related field. - Good understanding of Python and key libraries (NumPy, Pandas, Matplotlib, Scikit-learn). - Familiarity with basic optimization concepts (LP/MILP) and libraries like OR-Tools or Gurobi (student license). - Basic knowledge of reinforcement learning frameworks (OpenAI Gym, Stable-Baselines3) is a plus. - Strong problem-solving skills and willingness to learn advanced AI/OR techniques. In this role, you will gain hands-on exposure to real-world AI and optimization use cases in logistics and supply chain. You will receive mentorship from experienced scientists in OR, ML, and RL, and work in a fast-paced, applied research environment. There is also the opportunity to convert to a full-time role based on performance and business needs. (Note: The additional details about the company have been omitted as they were not directly related to the job description provided.),