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Data Scientist – Simulation (Senior - Principal)

Symbotic

USA Wilmington, MA - HQ, US$149k – $205khybrid

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About this role

Who we are With its A.I.-powered robotic technology platform, Symbotic is changing the way consumer goods move through the supply chain. Intelligent software orchestrates advanced robots in a high-density, end-to-end system – reinventing warehouse automation for increased efficiency, speed and flexibility.

What we need  

We are 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.  

What we do  

We design, test, and deploy advanced robotic systems that improve warehouse throughput, efficiency, and reliability at scale. By reducing reliance on physical testing, we accelerate innovation cycles and drive significant operational savings and productivity gains across real-world production environments. Our team tackles complex automation and optimization challenges alongside world-class engineers and scientists, with the opportunity to directly influence   cutting-edge   systems deployed in the field.  

What  y ou’ll  d o  

• 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.  

• 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.  

What you'll   need  

Required Qualifications  

• 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.

• Complex, distributed systems.

• Strong experience with:   

• Discrete-event simulation (DES)   or agent-based modeling.  

• Python   (NumPy, Pandas, SciPy) and/or simulation frameworks (e.g.,   SimPy ,   AnyLogic , Arena, or custom tools).  

• Solid understanding of:   

• Probability, stochastic processes, and statistics.  

• 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.  

Preferred Qualifications  

• 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.  

Principal-Level Expectations (in addition to above)  

• Define and drive the   long-term simulation and modeling strategy.

• Architect scalable simulation platforms used across the organization.

• Influence product and operational strategy through data-driven insights.

• Mentor and grow a team of data scientists and engineers.

• Serve as a subject matter expert in   simulation, optimization, and system modeling.

Tech Stack   

• Python (NumPy, Pandas, SciPy,   SimPy ).  

• D ata platforms (Snowflake, Databricks).

• Visualization ( Grafana , Tableau).

• Cloud infrastructure (GCP).

• Optional:   Python,   C#   and   C++.

 Our environment  

•   Up to 10% of travel may be   required . Employees must have a valid driver’s license and the ability to drive and/or fly to client and other customer locations.   

• The employee   is responsible for   owning a credit card and managing expenses personally to be reimbursed on a bi-weekly basis.  

#LI-JS1 #LI-Hybrid

About Symbotic Symbotic is an automation technology leader reimagining the supply chain with its end-to-end, AI-powered robotic and software platform. Symbotic reinvents the warehouse as a strategic asset for the world’s largest retail, wholesale, and food & beverage companies. Applying next-gen technology, high-density storage and machine learning to solve today's complex distribution challenges, Symbotic enables companies to move goods with unmatched speed, agility, accuracy and efficiency. As the backbone of commerce the Symbotic platform transforms the flow of goods and the economics of supply chain for its customers. For more information, visit  www.symbotic.com .   We are a community of innovators, collaborators and pioneers who embrace our differences, because we know unique perspectives make us stronger and smarter. Every perspective matters. We depend on the collective voices of our employees, customers and community to help guide us as we build a better place to work – for you and the world. That’s why we’re proud to be an equal opportunity employer.  We do not discriminate based on

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