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Intern Computer Science Volunteer Jobs in Waltham, MA

L3HHCM20

Intern C, Systems Engineer

Wilmington, MA · On-site

$25.50 - $48/hr

Intern, Systems Engineering Job Code: 42844 Job Location: Wilmington, MA Job Schedule: 9/80 ... Computer Science, Physics, Mathematics, Aviation, Aerospace Engineering, or related fieldat an ...

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All JobsIntern Computer Science Volunteer JobsIntern Computer Science Volunteer Jobs in Waltham, MA

Intern Computer Science Volunteer information

See Waltham, MA salary details

$9

$18

$26

How much do intern computer science volunteer jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for intern computer science volunteer in Waltham, MA is $18.38, according to ZipRecruiter salary data. Most workers in this role earn between $15.58 and $20.77 per hour, depending on experience, location, and employer.

What is an intern computer science volunteer?

Intern Computer Science Volunteers are students or recent graduates who offer their time and skills to support organizations in technology-related projects without monetary compensation. They typically assist with programming, software development, data analysis, and IT support tasks under the guidance of experienced professionals. These roles provide practical experience, enhance technical skills, and offer networking opportunities, helping volunteers build their resumes and prepare for future careers in computer science.

What types of projects or tasks can an intern computer science volunteer expect to work on?

As an Intern Computer Science Volunteer, you may be involved in a variety of projects such as assisting with software development, performing data analysis, supporting IT infrastructure, or developing tools to improve organizational processes. Tasks often include collaborating with more experienced engineers, writing and testing code, troubleshooting technical issues, and participating in team meetings or code reviews. This role provides a valuable opportunity to gain hands-on experience, build your portfolio, and learn industry best practices in a supportive, educational environment.

What are the key skills and qualifications needed to thrive as an intern computer science volunteer, and why are they important?

To thrive as an Intern Computer Science Volunteer, you typically need foundational programming skills, problem-solving ability, and a relevant educational background in computer science or a related field. Familiarity with coding languages such as Python or Java, version control systems like Git, and basic software development tools is common. Strong communication, teamwork, and a willingness to learn are important soft skills for collaboration and adaptation in dynamic environments. These skills and qualities are crucial for contributing effectively to projects, gaining valuable experience, and supporting organizational goals.

What is the difference between Intern Computer Science Volunteer vs Intern Software Developer?

AspectIntern Computer Science VolunteerIntern Software Developer
Required CredentialsBasic programming knowledge, often no formal degree requiredSome programming experience, often pursuing or holding a computer science degree
Work EnvironmentNon-profit, educational, or community projectsTech companies, startups, or software firms
Employer & Industry UsageVolunteer organizations, NGOs, educational institutionsPrivate companies, tech industry, software development firms
Search & Comparison IntentUnderstanding volunteer opportunities in CSGaining software development experience as an intern

Intern Computer Science Volunteers typically engage in unpaid, community-focused projects requiring basic programming skills, often within non-profit or educational settings. Intern Software Developers usually work in paid internships within tech companies, focusing on software development tasks. While both roles involve programming, the main differences lie in the work environment, compensation, and industry context.

Intern Computer Science Volunteer jobs near you

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA • On-site

Full-time

Re-posted 28 days ago

Job description

Ph.D. Graduate Intern – Quantitative Portfolio Risk Analytics (Cross-Disciplinary)

Position Overview
We are seeking an exceptional Ph.D. graduate student to join our team as a Quantitative Portfolio Risk Analytics Intern. This role focuses on developing and applying advanced analytical methods to understand portfolio risk, market structure, and complex financial systems.
We are intentionally recruiting from cross-disciplinary, research-driven backgrounds. Doctoral candidates from fields such as physics, astrophysics, math, applied mathematics, statistics, engineering, economics, computer science, quantum computing, biotech, and other data-intensive sciences are strongly encouraged to apply—especially those interested in translating rigorous quantitative methods into real-world financial applications.
Key Responsibilities
  • Develop and enhance quantitative models for portfolio risk, including factor-based and statistical approaches 
  • Analyze large, high-dimensional financial datasets to uncover structure, dependencies, and sources of risk 
  • Design and implement analytical tools and pipelines using Python and SQL 
  • Contribute to model validation, backtesting, and performance evaluation 
  • Collaborate with risk, engineering, and data teams to improve model scalability and data infrastructure 
  • Communicate complex quantitative insights through clear visualizations and technical summaries 
  • Apply advanced methodologies from your discipline (e.g., stochastic modeling, optimization, machine learning, or geometric/topological approaches) to improve risk analytics 
Required Qualifications
  • Currently enrolled in a graduate Ph.D. program in a highly quantitative field (e.g., Math, Applied Mathematics, Physics, Astrophysics, Statistics, Computer Science, Engineering, Financial Engineering, Economics, Biotech or other data-driven disciplines) 
  • Strong foundation in probability, statistics, and numerical methods 
  • Proficiency in Python (NumPy, pandas, or similar) and/or SQL 
  • Experience working with large datasets and implementing quantitative models 
  • Ability to think rigorously about complex systems and translate theory into practical solutions 
Preferred Qualifications
  • Familiarity with quantitative finance concepts (e.g., portfolio theory, factor models, volatility modeling, Value-at-Risk) 
  • Experience with scientific computing, optimization, or machine learning 
  • Background or research in cross-disciplinary areas such as: 
    • Statistical physics, complex systems, or network theory 
    • Applied or computational mathematics 
    • Machine learning or probabilistic modeling 
    • Quantum computing or advanced optimization techniques 
    • Topological data analysis or geometric data methods 
  • Prior research, publications, or project work demonstrating advanced quantitative modeling 
What You’ll Gain
  • Exposure to real-world portfolio risk problems at the intersection of finance and advanced analytics 
  • Opportunity to apply cutting-edge academic methods in a production environment 
  • Collaboration with a highly quantitative, cross-disciplinary team 
  • Experience working with large-scale financial data and modern analytics infrastructure 
  • Mentorship and potential pathway to full-time quantitative roles 
Duration & Compensation
  • Internship: Summer 2026, with potential to extend 
  • Paid internship (competitive, based on experience and location)