Staff OR Scientist

GreyOrange · Gurgaon

Source and collection record

Last observed by our collector: 8 October 2026 at 11:28 pm IST. This is not a manual review or a confirmation from the employer.

Employer requisition: 10516

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Collected role description

We are seeking a highly skilled and innovative Principal Scientist - Operations Research & Simulation to lead the development of advanced simulation platforms and optimization algorithms for complex, automated fulfillment environments. This role requires a deep understanding of operations research, optimization theory, and simulation modeling, with a strong focus on solving NP-hard scheduling and orchestration challenges. Key Responsibilities: Lead the design and development of advanced simulation and emulation platforms that accurately replicate complex fulfillment environments, including automation systems, human workflows, and software orchestration layers. Architect and implement robust optimization algorithms utilizing operations research techniques such as linear programming, dynamic programming, heuristics, and stochastic models. Develop and apply solutions for NP-hard problems related to scheduling, resource allocation, and orchestration using constraint-based and temporal planners, as well as commercial solvers (e.g., Gurobi, CPLEX). Conduct in-depth analysis of large-scale performance data to identify inefficiencies, extract actionable insights, and recommend data-driven improvements in throughput, accuracy, and system stability. Collaborate cross-functionally with software engineering, robotics, and operations teams to integrate simulation models and optimization algorithms into live production systems. Design and validate digital twins that offer predictive capabilities and support scenario planning and what-if analysis for future deployments. Leverage expertise in simulation frameworks and tools (e.g., AnyLogic, FlexSim, Simio, or custom-built environments in Python/C++) to develop high-fidelity models for continuous performance evaluation. Develop and maintain analytics solutions, data pipelines, and optimization engines using strong programming skills in Python, R, and SQL. Apply deep domain knowledge of automated warehouse operations, robotics orchestration, and human-machine interaction to ensure simulation fidelity and real-world applicability.

Collected experience requirement

8-12 years