Symbotic · 채용 중 125건
Data Scientist – Simulation (Senior – Principal)
Data Scientist – Simulation (Senior – Principal)
데이터 사이언티스트정규직시니어 · 5~15년
Symbotic에서 차세대 로봇 창고 시스템을 위한 시뮬레이션 모델을 개발할 시니어/프린시펄 데이터 사이언티스트를 채용합니다. 이산 사건 시뮬레이션(DES) 및 에이전트 기반 모델링 경험이 필수이며, 복잡한 물류 환경의 최적화와 디지털 트윈 구축을 주도하게 됩니다. 로봇 공학 및 운영 연구 분야의 전문성을 갖춘 분들의 많은 지원 바랍니다.
USA Wilmington, MA - HQ
Time type: full time Posted on: May 19, 2026 Job requisition id: R7175
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.
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.
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.
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.
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., SimPyAnyLogic, 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.
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.
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.
Python (NumPy, Pandas, SciPy, SimPy
Data platforms (Snowflake, Databricks).
Visualization (Grafana, Tableau).
Cloud infrastructure (GCP).
Optional: Python, C# and C++.
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.
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The base range for this position in the posted location is $149,000.00 - $204,600.00 however, base pay offered may vary depending on job-related knowledge, skills, and experience. The compensation package includes medical, dental, vision, disability, 401K, PTO and/or other benefits.
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