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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 ...

pony.ai

(Senior) Software Engineer - Evaluation

Fremont, CA · On-site

$120K - $250K/yr

Strong foundation in mathematics and theoretical computer science, such as linear algebra, calculus, graph theory, computational geometry, combinatorial optimization algorithms, stochastic processes ...

Leidos

Senior Signal Processing Engineer

Arlington, VA

$180K - $270K/yr

... stochastic processes - Demonstrated leadership of small multi-disciplinary technical teams and/or projects - Demonstrated strong oral and written communication - Experience working in EW, SIGINT and ...

OPTWISE CONSULTING LLC

Be Seen First

Quant Finance Career Coach

New York, NY · Remote

$40 - $50/hr

Stochastic Processes Programming * Python * C++ * SQL * Data Structures * Algorithms Quant Topics * Options * Derivatives * Portfolio Theory * Market Microstructure * Time Series * Machine Learning

Leidos

Senior Signal Processing Engineer

Arlington, VA · On-site

$180K - $270K/yr

... stochastic processes - Demonstrated leadership of small multi-disciplinary technical teams and/or projects - Demonstrated strong oral and written communication - Experience working in EW, SIGINT and ...

Leidos

Signal Processing Engineer

National City, CA · On-site

$87K - $157K/yr

... and stochastic processes - Demonstrated strong oral and written communication - Ability to work in a team environment, as well as independently - Adaptability to new challenges with a strong ...

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Stochastic Processes information

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How much do stochastic processes jobs pay per year?

As of Jul 22, 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 jobs use stochastic processes?

Stochastic processes are used in various fields such as finance, engineering, data science, and operations research. Common jobs include quantitative analyst, financial engineer, data scientist, risk analyst, and operations researcher, all of which require modeling uncertainty and analyzing random systems using probabilistic methods and statistical tools.

What are the four types of stochastic processes?

In stochastic processes, the four main types are discrete-time and continuous-time processes, each classified as either stationary or non-stationary. Examples include Markov processes, martingales, and Poisson processes, which are commonly studied in fields like finance, engineering, and data analysis. Understanding these types helps in modeling and analyzing random phenomena effectively.

Is stochastic calculus the hardest math?

Stochastic calculus is a complex area of mathematics used in quantitative finance, engineering, and physics, involving advanced concepts like stochastic differential equations. Its difficulty depends on a person's background in calculus, probability, and differential equations; for some, it is among the more challenging topics in applied mathematics. Mastery often requires strong analytical skills and experience with mathematical modeling.

What is an example of a stochastic process in real life?

A stochastic process in the context of stochastic processes involves random variables evolving over time. An example is stock market price movements, which fluctuate unpredictably and are modeled using probabilistic methods. Such processes are studied in fields like finance and engineering to analyze systems with inherent randomness.

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.

More about Stochastic Processes jobs
What are the most commonly searched types of Stochastic Processes jobs? The most popular types of Stochastic Processes jobs are:
What job categories do people searching Stochastic Processes jobs look for? The top searched job categories for Stochastic Processes jobs are:
Stochastic Processes jobs near you
Infographic showing various Stochastic Processes job openings in the United States as of July 2026, with employment types broken down into 87% Full Time, 11% Part Time, and 2% Contract. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution, with an average salary of $84,057 per year, or $40.4 per hour.

Data Scientist Opportunity

Bridge Tech

Boston, MA • On-site

Full-time

Re-posted 28 days ago

Job description

Company Description
Job Description
The Data Science team is responsible for managing all data analytics, reporting and algorithmic aspects for our client. The data science team is an integral part of every function in the life cycle of the company to provide product, tools, business support. As a data scientist you will work closely with architects, engineers, account managers and data scientists within and outside the company. You will be involved from pre-sales to support. You will work on next generation algorithms development and help measure, maintain and upgrade current business.
Qualifications
REQUIRED SKILLS
Outstanding technical abilities with 5+ years of Scala, Java, or C/C++ development experience with statistical machine learning models
Rounded business skills with the ability to understand customer business needs
Ability to solve problems practically for clients and internal needs
Excellent interpersonal skills with ability to communicate clearly and concisely with executives, engineers, account managers, sales, business partners and data scientists.
Ability to respond to customer needs and meet deadlines with accurate work while under pressure
Expected to build statistical, optimization and machine learning models followed by detailed pre-production out of sample validation and recommendation for a/b testing experiments with success criteria.
Own complete life cycle from problem formulation to solution deployment and maintenance
Excellent understanding of computer science fundamentals, data structures, and algorithms
Have a strong mathematical background and have experience with modeling complex high dimensional problems
Experience performing petabyte scale data analysis and developing meaningful visualizations
Must be able to collaborate with architects, engineers, and data scientists within and outside the company.
EXPERIENCE
Proven to thrive in start up environments
Experience defining and building web scale algorithms, reports and visualizations
Must be organized, have an eye for detail, and be able to put ideas into a tangible form
Ability to prioritize and manage work to critical project timelines in a fast-paced environment and the ability to develop new approaches to complex design problems
Experience with developing production grade algorithms for the web scale
Preferred - Ph.D. in Computer Science, Operations Research, Physics, Electrical Engineering, Mathematics or other quantitative fields.
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 information will be kept confidential according to EEO guidelines.

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