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Stochastic Processes Internship Jobs (NOW HIRING)

Weiss Asset Management

Investment Analyst

Boston, MA · On-site

$135K - $200K/yr

... internships) with the following: * Financial modeling techniques including discounted cash flow ... Probability theory, statistical inference, linear regression, and stochastic processes applied to ...

Weiss Asset Management

Investment Analyst

Boston, MA

$135K - $200K/yr

... internships) with the following: * Financial modeling techniques including discounted cash flow ... Probability theory, statistical inference, linear regression, and stochastic processes applied to ...

General Atomics

Data Scientist III

Charlottesville, VA · On-site

$98K - $171K/yr

Expertise in stochastic processes and time series analysis * Proficiency in Python, MATLAB, R, or ... Prior internships or collaborations with defense, aerospace, or robotics organizations * Experience ...

General Atomics

Data Scientist III

Charlottesville, VA · On-site

Expertise in stochastic processes and time series analysis * Proficiency in Python, MATLAB, R, or ... Prior internships or collaborations with defense, aerospace, or robotics organizations * Experience ...

Aon

Early Careers: Actuarial Intern

Wayne, PA · On-site

Crafting projections (both stochastic and deterministic) of long-term financial information for ... Our interns collaborate directly with clients to develop welfare benefit strategies. This process ...

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How much do stochastic processes internship jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for stochastic processes internship in the United States is $15.54, according to ZipRecruiter salary data. Most workers in this role earn between $12.50 and $17.55 per hour, depending on experience, location, and employer.

What types of projects or problems do interns typically work on during a stochastic processes internship?

During a Stochastic Processes Internship, interns often engage in projects that involve modeling uncertainty and randomness using advanced mathematical and statistical techniques. This may include tasks such as analyzing real-world data, simulating random processes, or assisting in the development of algorithms for fields like finance, engineering, or data science. Interns frequently collaborate with senior researchers or analysts to solve practical problems, present findings, and may contribute to ongoing research or product development. The work environment is usually collaborative and may involve regular meetings to discuss progress and share insights.

What is a stochastic processes internship?

A Stochastic Processes Internship is a temporary position that allows students or recent graduates to gain practical experience working with random processes and probabilistic models. Interns typically assist with research, data analysis, simulations, and modeling tasks using mathematical and statistical techniques to analyze systems that evolve over time in a random manner. These internships are common in industries such as finance, insurance, data science, and engineering, where understanding uncertainty and randomness is crucial. Interns often work under the supervision of experienced researchers or professionals, and the experience helps them build both technical skills and industry knowledge.

What are the key skills and qualifications needed to thrive as a stochastic processes intern, and why are they important?

To thrive as a Stochastic Processes Intern, you need a solid understanding of probability theory, statistics, and advanced mathematics, typically supported by coursework or a degree in mathematics, statistics, or related fields. Familiarity with programming languages like Python or R, statistical software, and tools such as MATLAB is often required. Strong analytical thinking, attention to detail, and effective communication are standout soft skills for this role. These skills and qualifications are crucial for analyzing complex random systems, communicating findings, and contributing to research or applied projects.

What is the difference between Stochastic Processes Internship vs Data Analyst Internship?

AspectStochastic Processes InternshipData Analyst Internship
Required CredentialsUndergraduate or graduate in mathematics, statistics, or related fieldsUndergraduate or graduate in statistics, data science, or related fields
Work EnvironmentResearch-focused, often in finance, insurance, or academiaBusiness, finance, or tech companies analyzing data sets
Industry UsageFinance, academia, research institutionsBusiness, marketing, finance, tech
Common Search/ComparisonYesYes

The main difference between a Stochastic Processes Internship and a Data Analyst Internship lies in focus and application. A Stochastic Processes Internship emphasizes mathematical modeling and probability theory, often in research or finance sectors. In contrast, a Data Analyst Internship centers on analyzing data to inform business decisions. Both roles require strong analytical skills and related educational backgrounds, but their industry applications and daily tasks differ significantly.

More about Stochastic Processes Internship jobs
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Stochastic Processes Internship jobs near you
Infographic showing various Stochastic Processes Internship job openings in the United States as of August 2026, with employment types broken down into 13% Internship, 49% Full Time, and 38% Part Time. Highlights an 87% In-person, and 13% Remote job distribution, with an average salary of $32,333 per year, or $15.5 per hour.

Research Intern - Advanced Wireless Technology Development for 6G Networks

Futurewei

Schaumburg, IL • On-site

Other

Re-posted 12 days ago

Job description

Fall Intern Position

Futurewei is expanding leadership in creating innovative networking technologies for 6G wireless networks. We are seeking Fall interns to focus on PHY layer research into wireless networking and technology for 6G Radio Access Networks.

Responsibilities:

  1. Our intern will focus on research into wireless networking and technology for 6G Radio Access Networks.
  2. The program goal will be to develop and demonstrate novel concepts for advanced wireless networks utilizing cutting-edge communication theory techniques, drawing from advances in optimization and signal processing techniques, and built upon our existing research outcomes in these areas.
  3. A range of research activities are available to pursue in this important area. These have been identified as part of our recent research work and include advanced MIMO/BF communication, network energy saving, PHY layer signal and receiver design in mobile networks, etc.

Requirements:

  • Completion of applicable graduate coursework in relevant fields within electrical engineering and/or applied mathematics, e.g., wireless communication, signal processing, stochastic processes, communications networks, and optimization. Doctoral students with completion of master's degree, in Electrical Engineering, Computer science and/or Applied Mathematics are preferred.
  • Candidate should have knowledge in wireless networks, and knowledge and previous experience in reference signal design, MIMO/Beamforming and its performance evaluation for wireless communications.
  • Excellent communication and teamwork skills.
  • Proficiency with commercial programming/processing tools, e.g., MATLAB, Python.

Location:

Schaumburg, IL

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