Operations Research Scientist

As an Operations Research Scientist at GreyOrange , you will be responsible for designing, developing, and validating advanced models and algorithms to solve optimization problems at the core of large-scale warehouse automation utilizing heterogeneous robot fleets. You will collaborate with cross-functional teams, including product management, development, testing, and implementation, to optimize processes, improve product performance, and solve complex problems using state-of-the-art mathematical and computational methods. The ideal candidate will have a deep understanding of optimization algorithms, stochastic modeling, multi-agent systems, and machine learning, along with proficiency in simulation modeling to analyze complex warehouse environments. Roles and responsibilities

• Develop and apply advanced operations research models, including optimization, simulation, and stochastic models, to solve complex system performance challenges, particularly in the areas of VRP, MAPF, order processing, task scheduling, queuing strategy, efficient slotting, and stock replenishment.
• Work closely with engineering, data science, and product teams to integrate OR models and algorithms into the GreyMatter system, providing actionable insights to enhance product performance.
• Design and implement optimization algorithms (e.g., linear programming, mixed-integer programming, and nonlinear optimization) to drive efficiency and performance goals.
• Analyze large datasets and develop predictive models using statistical and machine learning techniques to improve decision-making processes.
• Develop mathematical models, simulations, or optimization algorithms to represent real-world systems or problems. Use techniques like linear programming, dynamic programming, queuing theory, or game theory to create models.
• Build simulation models to evaluate the performance of the models and algorithms under different conditions.
• Collaborate with stakeholders to understand business requirements and translate them into mathematical models and algorithmic solutions.
• Communicate complex mathematical concepts, insights, and recommendations to non-technical stakeholders through reports, presentations, or data visualizations.
• Monitor the performance of implemented solutions in test setups as well as in production, and refine models over time based on feedback and new data.
• Stay updated with the latest advancements in operations research, machine learning, and optimization, and apply best practices to develop innovative solutions.
• Document models, algorithms, and analytical processes for future reference and team knowledge sharing. Generate reports that summarize the outcomes of analyses and model performance.

Requirements/Qualifications

• Master’s or Ph.D. in Operations Research, Applied Mathematics, Industrial Engineering, Computer Science, Robotics, or a related field.
• Strong expertise in mathematical modeling, optimization techniques (linear programming, dynamic programming), and statistical analysis.
• Strong background in multi-agent systems, path planning, and Discrete Event Simulation (DES).
• Proficiency in programming languages such as Python, R, C++, and experience with optimization tools (Gurobi, CPLEX, OptaPlanner, MATLAB).
• Familiarity with data analysis, machine learning techniques, and simulation.
• Excellent problem-solving skills and the ability to translate complex problems into actionable insights.
• Strong collaboration skills and the ability to communicate complex concepts to non-technical stakeholders.
• Experience managing or contributing to research projects in a fast-paced environment.
• Experience working in robotics, logistics, warehouse operations, or supply chain environments is highly desirable.

GreyOrange is a global leader in AI-driven robotic automation software and hardware, transforming distribution and fulfillment centers worldwide. Our solutions increase productivity, empower growth and scale, mitigate labor challenges, reduce risk and time to market, and create better experiences for customers and employees. Founded in 2012, GreyOrange is headquartered in Atlanta, Georgia, with offices and partners across the Americas, Europe and Asia. Our Solutions The GreyMatter Multiagent Orchestration (MAO) platform provides vendor-agnostic fulfillment orchestration to continuously optimize performance in real time: the right order, with the right bot and agent, taking the right path and action. Currently operating more than 70 fulfillment sites across the globe (with deployments of 700+ robots at a single site), GreyMatter enables customers to decrease their fulfillment Cost Per Unit by 50%, reduce worker onboarding time by 90% and optimize peak season performance. In retail stores, our gStore end-to-end store execution and retail management solution supports omnichannel fulfillment, real-time replenishment, intelligent workforce tasking and more. Using real-time overhead RFID technology, the platform increases inventory accuracy up to 99%, doubles staff productivity, and enables an engaging, seamless in-store experience.