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Stochastic Processes Internship Jobs (NOW HIRING)

Roku

Senior Data Scientist

New York, NY · On-site +1

$126K - $199K/yr

Must have prior experience, internship, project background, or advance level coursework in each of ... Processing, and Deep Learning Model. * Mathematical and Optimization Models, including Stochastic ...

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How much do stochastic processes internship jobs pay per hour?

As of Sep 1, 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 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 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 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.

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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 87% Full Time, 10% Part Time, 2% Contract, and 1% Nights. Highlights an 90% Physical, 3% Hybrid, and 7% Remote job distribution, with an average salary of $32,333 per year, or $15.5 per hour.

Research Statistician - Tracking and Estimation Theory

General Atomics

Charlottesville, VA • On-site

Full-time

Re-posted 3 days ago

General Atomics rating

9.0

Company rating: 9.0 out of 10

Based on 39 frontline employees who took The Breakroom Quiz

10th of 72 rated aerospace companies

Job description

Job Summary
Are you a statistician who wants to see your Bayesian models protect national security?
GA-Intelligence is seeking a Statistics PhD to develop tracking algorithms that process data from heterogeneous sensors, fuse tracks across domains, and enable time-critical intelligence decisions. You'll apply statistical inference, state-space modeling, and Monte Carlo methods to multi-target tracking challenges that combine mathematical rigor with operational constraints.
Your work will span algorithm research, operational analysis, and production deployment-from deriving novel filters to validating performance on classified sensor data to partnering with engineers who implement your algorithms at scale.
DUTIES AND RESPONSIBILITIES:
Algorithm Research and Development:
  • Guide the development of state-of-the-art tracking algorithms from existing tracking literature, ensuring technical correctness.
  • Develop statistical approaches to data association in multi-target, multi-sensor environments
  • Derive probabilistic models for target behavior and sensor measurement processes
  • Prototype algorithms in Python, MATLAB, or R and validate performance through Monte Carlo simulation
  • Apply modern statistical and computational methods to emerging tracking challenges

Operational Impact:
  • Collaborate with intelligence analysts to understand tracking requirements and operational constraints
  • Analyze tracking performance on real-world sensor data from classified systems
  • Quantify and communicate uncertainty, assumptions, and limitations to support operational decision-making
  • Translate operational gaps into tractable statistical problems
  • Partner with software engineers to transition algorithms from prototype to production

Research Leadership:
  • Publish internal research on tracking advances and algorithmic innovations
  • Present findings to technical staff, program managers, and government decision-makers, as well as external conferences
  • Contribute to proposal development and help shape future research directions
  • Mentor junior team members and future hires
  • Stay current with tracking research literature and evaluate applicability to operational problems
We recognize and appreciate the value and contributions of individuals with diverse backgrounds and experiences and welcome all qualified individuals to apply.
Job Qualifications
  • Typically requires a bachelor's degree, master's degree or PhD in data science, applied mathematics, statistics, computer science, or related technical/quantitative discipline from an accredited institution and progressive data science experience as follows; five or more years of experience with a bachelor's degree, three or more years of experience with a master's degree, or one or more years with a PhD. May substitute equivalent experience in lieu of education.
  • Strong preference for PhD in Statistics, Biostatistics, or closely related quantitative field
  • Dissertation research in Bayesian inference, state-space modeling, sequential estimation, or time series analysis
  • Strong foundations in statistical inference, probability theory, statistical modeling, and Bayesian methods
  • Deep understanding of state-space models, Kalman filtering, and sequential Monte Carlo methods
  • Expertise in stochastic processes and time series analysis
  • Proficiency in Python, MATLAB, R, or similar scientific computing languages
  • Experience implementing statistical algorithms and conducting simulation studies
  • Strong analytical and problem-solving abilities
  • Ability to communicate complex statistical concepts clearly to technical and non-technical audiences
  • Curiosity about operational applications and mission context
  • Collaborative mindset-works well with software engineers, intelligence analysts, and researchers
  • Ability to obtain and maintain a DoD security clearance is required.

Preferred Qualifications:
Domain Experience:
  • Familiarity with tracking, navigation, or multi-target systems
  • Experience with sensor fusion or data association problems
  • Knowledge of Extended Kalman Filters, Unscented Kalman Filters, particle filters, or IMM filters
  • Understanding of coordinate transformations and reference frames

Research Background:
  • Contributed to peer-reviewed publications, technical reports, or conference presentations
  • Experience with probabilistic programming frameworks
  • Dissertation work involving real-world sensor data or applied problems
  • Prior internships or collaborations with defense, aerospace, or robotics organizations
  • Experience writing technical proposals for government research projects
  • Experience leading technical projects or mentoring junior researchers

Technical Breadth:
  • Programming experience in one or more languages such as Python, C++, Java
  • High-performance computing or numerical optimization
  • Version control (Git) and collaborative development practices
  • Exposure to real-time systems or computational constraints

Why Join GA-Intelligence
Operational Impact: Your tracking algorithms will run in production systems supporting intelligence analysts and military personnel. Your work directly contributes to national security missions.
Technical Challenge: Multi-target tracking in adversarial environments with heterogeneous sensors is an unsolved research problem. You'll tackle cutting-edge algorithmic challenges that combine statistical rigor with operational constraints.
Collaborative Environment: Work alongside tracking mathematicians, software engineers, intelligence analysts, and mission experts. We value diverse perspectives and believe the best solutions emerge from multidisciplinary collaboration. Our team is committed to advancing the state-of-the-art in tracking while maintaining a culture of innovation, integrity, and teamwork.
Research Opportunities: Continue publishing research, present at conferences, and contribute to the tracking research community while delivering operational capabilities.
Charlottesville Location:
  • Blue Ridge Mountains and Shenandoah National Park (30 minutes)
  • University town culture with intellectual community (University of Virginia)
  • Short average commute (no DC Beltway traffic)

Career Growth:
  • Build and lead tracking algorithm research team over time
  • Technical leadership opportunities
  • Shape strategic direction of tracking capabilities

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About General Atomics

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General Atomics (GA), and its affiliated companies, is one of the world's leading resources for high-technology systems development ranging from the nuclear fuel cycle to remotely piloted aircraft, airborne sensors, and advanced electric, electronic, wireless and laser technologies.

Industry

Space research administration

Company size

10,000+ Employees

Headquarters location

San Diego, CA, US

Year founded

1955

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