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Stochastic Modeling Jobs (NOW HIRING)

BAE Systems

Ops Research Anst Sr Prin II

Kingsport, TN · On-site +1

$99K - $136K/yr

Create stochastic modeling and measuring techniques, utilizing mathematics, statistical methods, engineering methods, operational mathematics techniques, and other principles and laws of scientific ...

Popular Tech

Data Scientist

Irvine, CA · On-site

$101K/yr

Use Python, PySpark, Streamlit, & SQL; apply Stochastic Modeling, Time-Series Forecasting, & Statistical Analysis; A/B testing, Hypothesis-Driven Analysis, & Model Eval & Performance Monitoring;

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$25.5K

$104.4K

$201.5K

How much do stochastic modeling jobs pay per year?

As of Sep 14, 2026, the average yearly pay for stochastic modeling in the United States is $104,419.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,500.00 and $128,000.00 per year, depending on experience, location, and employer.

What is stochastic modeling?

A Stochastic Modeling job involves developing mathematical models that incorporate randomness to analyze uncertain systems and predict outcomes. Professionals in this field apply probability theory, statistics, and computational techniques to fields such as finance, insurance, engineering, and data science. They build and validate models to assess risks, optimize decision-making, and improve forecasting accuracy. Strong analytical skills and proficiency in programming languages like Python, R, or MATLAB are often required.

What does someone in stochastic modeling do?

As a stochastic modeling professional, your daily tasks might include developing and validating probabilistic models, analyzing large datasets, and performing simulations to forecast outcomes or assess risks. You’ll often collaborate with cross-functional teams such as data scientists, financial analysts, or engineers to translate real-world problems into mathematical frameworks. Regular responsibilities also involve presenting findings to stakeholders, refining models based on new data, and staying updated on the latest modeling techniques in your industry. This role provides a balance of independent analytical work and teamwork, offering diverse challenges and skill development opportunities.

What are the key skills and qualifications needed for stochastic modeling?

To thrive in stochastic modeling, you need strong mathematical and statistical skills, often backed by a degree in mathematics, statistics, data science, or a related field. Expertise with technical tools such as R, Python, MATLAB, and statistical modeling software, as well as familiarity with industry-standard certifications like FRM or CFA in finance, is highly valued. Analytical thinking, attention to detail, and the ability to communicate complex ideas to non-technical stakeholders are critical soft skills. These competencies allow you to create accurate models for forecasting and risk assessment, helping organizations make informed decisions in uncertain environments.

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Stochastic Modeling jobs near you
Infographic showing various Stochastic Modeling job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 86% Full Time, 11% Part Time, and 2% Contract. Highlights an 80% Physical, 4% Hybrid, and 16% Remote job distribution, with an average salary of $104,419 per year, or $50.2 per hour.

Principal Research Scientist, Amazon Connect

New York, NY • On-site

Amazon
IT Services • 10K+ employees
Learn more about Amazonexternal

Full-time

Re-posted 4 days ago

Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 7,180 frontline employees who took The Breakroom Quiz

Job description

Do you want to define the scientific direction for how a global contact-center network forecasts demand, schedules its workforce, and optimizes operations in real time. The Eliza team within Amazon Connect (FCS) is looking for a Principal Research Scientist with a deep operations research specialization to set the research agenda in operations science - combinatorial optimization, queueing theory, stochastic modeling, and forecasting - and to translate that research into production systems that serve millions of customer interactions.
As a Principal Research Scientist, you will be the senior technical voice for operations research across the org. You will identify the highest-leverage scientific problems, architect novel solutions, and drive them from research through production deployment

You will not sit apart from the work - you will remain deeply hands-on with data, models, and systems while raising the scientific bar for scientists and engineers around you. This is an individual-contributor Principal role: your influence comes from technical depth, invention, and the ability to move business and engineering roadmaps through scientific rigor.
You will operate at the intersection of demand forecasting, workforce scheduling, and network optimization - applying combinatorial optimization to large-scale scheduling and resource-allocation problems and queueing theory to model contact-center dynamics under uncertainty, non-stationarity, and competing operational constraints at Internet scale - turning that reasoning into systems that continuously sense, predict, and optimize.
Key job responsibilities
- Set the multi-year research direction for operations research across contact-center demand prediction, workforce scheduling, and network optimization.
- Design and deliver novel algorithms in combinatorial optimization (large-scale scheduling, resource allocation, integer/constraint programming) and queueing theory (contact-center modeling, staffing under stochastic arrivals), alongside stochastic modeling and time-series forecasting, that advance the state of the art while solving real operational problems.
- Own end-to-end scientific solutions - from problem formulation and prototyping to production deployment - ensuring robustness, explainability, and seamless integration with existing systems.
- Design rigorous experiments and evaluation methodology to validate hypotheses and quantify business impact; establish scientific-excellence mechanisms (metrics, benchmarks, peer review) that the broader science team adopts.
- Partner with engineering, product, and operations teams to define data and logging requirements, get them prioritized on roadmaps, and translate scientific capabilities into measurable business outcomes.
- Influence senior leadership through written papers and deep-dives, framing complex algorithmic trade-offs in clear business terms.
- Mentor and raise the bar for applied and research scientists across the org while maintaining significant hands-on technical contribution.
- Represent the team's science externally where appropriate (publications, patents, top-tier venues such as INFORMS, NeurIPS, ICML).
A day in the life
Your day blends hands-on science with technical leadership. You might spend the morning deep in data and models - prototyping a new combinatorial-optimization formulation for workforce scheduling or a queueing model for staffing under stochastic arrivals against production infrastructure - and the afternoon guiding fellow scientists through a hard optimization or stochastic-modeling problem, reviewing an experiment design, or aligning engineering partners on the data architecture needed to unlock the next capability

You'll drive technical discussions with the team and key stakeholders, and periodically write and present papers that shape the business and engineering roadmap.

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About Amazon

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Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate, computer and electronic product manufacturing and software development

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US

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