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Stochastic Processes Jobs (NOW HIRING)

Bridge Tech

Data Scientist Opportunity

Boston, MA · On-site

Experience with Spark, Kaplan, Breeze, map/reduce models a plus Experience modeling stochastic processes, Bayesian learning models, utility theory, game theory a plus Additional Information All your ...

Bridge Tech

Data Scientist Opportunity

Boston, MA · On-site

Experience with Spark, Kaplan, Breeze, map/reduce models a plus Experience modeling stochastic processes, Bayesian learning models, utility theory, game theory a plus Additional Information All your ...

Howard University

Assistant Professor

Washington, DC · On-site

$110K - $125K/yr

Applied Statistics, Probabilistic/Bayesian Machine Learning, Deep Learning, Stochastic Processes, Stochastic Optimization, AI/ML for Business. • Teaching experience in: time series, data mining ...

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How much do stochastic processes jobs pay per year?

As of Jun 5, 2026, the average yearly pay for stochastic processes in the United States is $84,057.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,000.00 and $97,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Stochastic Processes position, and why are they important?

To excel in a Stochastic Processes role, you need a strong background in probability theory, mathematical modeling, statistical analysis, and typically a degree in mathematics, statistics, or a related quantitative field. Proficiency with tools such as MATLAB, R, Python, or specialized simulation software, as well as relevant certifications in data analysis or quantitative finance, is often required. Strong problem-solving abilities, attention to detail, and the ability to communicate complex concepts clearly are key soft skills in this field. These skills are vital to effectively analyze random systems, model uncertainty in real-world scenarios, and help guide data-driven decision-making across numerous industries.

What is a Stochastic Processes job?

A Stochastic Processes job typically involves working with mathematical models that incorporate randomness and uncertainty. Professionals in this field analyze and apply probabilistic methods to various domains, such as finance, engineering, machine learning, and operations research. Common tasks include developing statistical models, simulating random systems, and optimizing decision-making under uncertainty. These roles often require expertise in probability theory, programming, and statistical analysis.

What kinds of projects or problems do professionals working in stochastic processes typically address?

Professionals specializing in stochastic processes commonly tackle projects that involve modeling and predicting random systems, such as financial markets, inventory management, telecommunications networks, or biological processes. Typical responsibilities include developing and testing mathematical models, running simulations, analyzing large datasets, and providing actionable insights to support strategic business decisions. They often collaborate closely with data scientists, engineers, or business analysts depending on the industry, and their work can have a direct impact on optimizing operations or managing risk. Project scopes can range from short-term analyses to longer-term research and development initiatives, offering a dynamic and intellectually stimulating work environment.

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What are the most commonly searched types of Stochastic Processes jobs? The most popular types of Stochastic Processes jobs are:
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Stochastic Processes jobs near you
Infographic showing various Stochastic Processes job openings in the United States as of May 2026, with employment types broken down into 12% Locum Tenens, 35% As Needed, 2% Full Time, 27% Temporary, and 24% Nights. Highlights an 83% Physical, 6% Hybrid, and 11% Remote job distribution, with an average salary of $84,057 per year, or $40.4 per hour.
Data Scientist - Simulation (Senior - Principal)

Data Scientist - Simulation (Senior - Principal)

Symbotic

Wilmington, MA • Hybrid

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 17 days ago

Job description

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 experiencedSenior or Principal Data Scientistto 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,optimizesystem performance, and inform strategic product and operational decisions.

This is a highly cross-functional position spanningdata science, robotics, operations research, and distributed systems, where your work will directlyimpactefficiency, 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 influencecutting-edgesystems deployed in the field.

Whatyou'lldo

  • Design and develop simulation frameworksfor robotic warehouse systems, including robot fleets, inventory flows, task allocation, and human-robot interaction.

  • Builddiscrete-event and agent-based simulationsto model complex, stochastic environments at scale.

  • Developpredictive and prescriptive modelstooptimizethroughput, latency, and resourceutilization.

  • Partner with robotics, software, and operations teams to:

  • Evaluate new algorithms (routing, task assignment, scheduling).

  • Test system changes before production deployment.

  • Identifybottlenecks and failure modes.

  • Createdigital twinsof warehouse environments to enable scenario testing and capacity planning.

  • Applymachine learning and statistical techniquesto improve simulation realism and calibration.

  • Deliverclear insights and recommendationsto technical and executive stakeholders.

  • Establish best practices formodel validation, experimentation, and reproducibility.

What you'llneed

Required Qualifications

  • MS or PhD inComputer 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 withC++ or high-performance systemsfor 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 thelong-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 insimulation, optimization, and system modeling.

Tech Stack

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

  • Data platforms (Snowflake, Databricks).

  • Visualization (Grafana, Tableau).

  • Cloud infrastructure (GCP).

  • Optional:Python,C#andC++.

Our environment

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

  • The employeeis responsible forowning 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, visitwww.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 race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or genetic information.

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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