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Stochastic Processes Jobs (NOW HIRING)

pony.ai

Software Engineer Intern - Generalist

Fremont, CA · On-site

$7.0K - $10K/mo

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

Jay Analytix

Quantitative Developer

New York, NY · On-site

Solid grounding in probability, stochastic processes, and statistics. * Hands-on experience with pricing models, risk metrics, and financial data. Technical * Advanced Python, including NumPy, Pandas ...

The Pennsylvania State University

STAT 416 - Stochastic Modeling * STAT 418 - Introduction to Probability and Stochastic Processes for Engineering * STAT 460 - Intermediate Applied Statistics * STAT 461 - Analysis of Variance * STAT ...

Leidos

Signal Processing Engineer

Arlington, VA · 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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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.
Senior Manager Philadelphia (Hybrid) Full time role

Senior Manager Philadelphia (Hybrid) Full time role

Lorven Technologies

Philadelphia, PA • On-site

Full-time

Posted 19 days ago

Job description

Role: Senior Manager
Location: Philadelphia (Hybrid)
Experience: 5+ years
Full Time Role
Role Overview
We are looking for a Senior Manager - Data Science (Econometrics & Time Series) to lead advanced analytical initiatives for a major Telecommunications client.
This role is heavily focused on econometric modeling, time series analysis, and causal inference, with applications in forecasting, pricing, and customer behavior analytics. The ideal candidate brings deep expertise in statistical modeling and is comfortable working with large-scale data environments.
Key Responsibilities
  • Lead development of time series forecasting models (ARIMA, VAR, state-space models, etc.) for business-critical use cases.
  • Apply econometric techniques such as WLS, panel data models, and causal inference methods to solve real-world business problems.
  • Design and implement Bayesian models and probabilistic frameworks for uncertainty estimation and decision-making.
  • Utilize Markov chains and stochastic processes for modeling sequential or behavioral data.
  • Translate business problems into robust analytical frameworks and deliver actionable insights.
  • Work with large datasets using Databricks
  • Collaborate with stakeholders across business and technical teams to ensure model relevance and impact.
  • Mentor junior team members and drive best practices in statistical modeling and experimentation.

Must-Have Qualifications
  • Strong foundation in econometrics and time series analysis (this is critical for the role).
  • Hands-on experience with:
    • Time series models (ARIMA, SARIMA, VAR, forecasting techniques)
    • Econometric methods (WLS, regression diagnostics, panel data models)
    • Causal inference (A/B testing, quasi-experimental methods)
    • Bayesian statistics and probabilistic modeling
    • Markov chains or stochastic modeling
  • Proficiency in Python along with SQL.
  • Experience working with Databricks or similar big data platforms.
  • Ability to clearly communicate complex statistical concepts to non-technical stakeholders.

Secondary / Good-to-Have Skills (General Data Science)
  • Experience with machine learning models (classification, regression, tree-based models, etc.)
  • Familiarity with feature engineering, model validation, and performance tuning
  • Exposure to ML pipelines and MLOps concepts
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About Lorven technologies

Sourced by ZipRecruiter

Lorven Technologies, headquartered in Plainsboro, New Jersey, United States, is a reputable company in the technology industry, specializing in providing effective IT solutions and consulting services. The company's official website, lorventech.com, offers comprehensive insights into its offerings which include but are not limited to software development, IT consulting, project management, and business analysis. Since its inception, Lorven Technologies has been committed to ensuring efficiency and reliability in delivering IT services to its global clientele, establishing itself as a trusted name in the industry.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Plainsboro, NJ, US

Year founded

2001

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