Data Scientist – Simulation (Senior - Principal)

Exol•Wilmington, MA

21d•$149,000 - $204,600•Hybrid

About The Position

Symbotic is seeking an experienced Senior or Principal Data Scientist to lead the development of advanced simulation models that power next-generation robotic warehouse systems. In this role, you will build high-fidelity simulations of large-scale robotic fleets, optimize system performance, and inform strategic product and operational decisions. This is a highly cross-functional position spanning data science, robotics, operations research, and distributed systems, where your work will directly impact efficiency, throughput, and scalability of real-world automation systems.

Requirements

MS or PhD in Computer Science, Data Science, Operations Research, Applied Mathematics, Physics, or related field.
Minimum of 5 years (Senior) or minimum of 8 years (Principal) of experience in simulation, modeling, or systems optimization.
Minimum of 5 years (Senior) or minimum of 8 years (Principal) of experience in complex, distributed systems.
Strong experience with discrete-event simulation (DES) or agent-based modeling.
Strong experience with Python (NumPy, Pandas, SciPy) and/or simulation frameworks (e.g., SimPy, AnyLogic, Arena, or custom tools).
Solid understanding of probability, stochastic processes, and statistics.
Solid understanding of optimization techniques (LP, MIP, heuristics, metaheuristics).
Experience working with large datasets and building data pipelines.
Ability to translate real-world system behavior into computational models.

Nice To Haves

Robotics, warehouse automation, logistics, or supply chain systems.
Fleet optimization or multi-agent systems.
Reinforcement learning for decision-making.
Path planning, task allocation, and scheduling algorithms.
Digital twin architecture.
Experience with C++ or high-performance systems for large-scale simulation.
Knowledge of cloud platforms (AWS, Azure, GCP) and distributed computing.
Background in experimentation platforms or A/B testing in operational systems.

Responsibilities

Design and develop simulation frameworks for robotic warehouse systems, including robot fleets, inventory flows, task allocation, and human-robot interaction.
Build discrete-event and agent-based simulations to model complex, stochastic environments at scale.
Develop predictive and prescriptive models to optimize throughput, latency, and resource utilization.
Partner with robotics, software, and operations teams to evaluate new algorithms (routing, task assignment, scheduling), test system changes before production deployment, and identify bottlenecks and failure modes.
Create digital twins of warehouse environments to enable scenario testing and capacity planning.
Apply machine learning and statistical techniques to improve simulation realism and calibration.
Deliver clear insights and recommendations to technical and executive stakeholders.
Establish best practices for model validation, experimentation, and reproducibility.
Define and drive the long-term simulation and modeling strategy (Principal-Level).
Architect scalable simulation platforms used across the organization (Principal-Level).
Influence product and operational strategy through data-driven insights (Principal-Level).
Mentor and grow a team of data scientists and engineers (Principal-Level).
Serve as a subject matter expert in simulation, optimization, and system modeling (Principal-Level).