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Principal Scientist – Operations Research & Simulation

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Emerson United Inc- Strategic Search and Recruitment
Full Time position
Listed on 2026-07-10
Job specializations:
  • Research/Development
    Operations Research Analyst, Data Scientist
Salary/Wage Range or Industry Benchmark: 180000 - 300000 USD Yearly USD 180000.00 300000.00 YEAR
Job Description & How to Apply Below

Principal Scientist – Operations Research & Simulation

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 replicate complex fulfillment environments, including automation systems, human workflows, and orchestration layers.
  • Architect and implement robust optimization algorithms using 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 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 provide predictive capabilities and support scenario planning and what-if analysis for future deployments.
  • Leverage expertise in simulation frameworks and tools (e.g., Any Logic, Flex Sim, Simio, or custom-built environments in Python/C++) to build high-fidelity models for ongoing performance evaluation.
  • Develop and maintain analytics solutions, data pipelines, and optimization engines using strong programming skills in Python, R, and SQL.
  • Apply domain knowledge of automated warehouse operations, robotics orchestration, and human-machine interaction to ensure simulation fidelity and real-world applicability.
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