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Internship Numerical Methods Jobs in Boston, MA (NOW HIRING)

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Internship Numerical Methods information

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$11

$19

$31

How much do internship numerical methods jobs pay per hour?

As of Sep 8, 2026, the average hourly pay for internship numerical methods in Boston, MA is $19.08, according to ZipRecruiter salary data. Most workers in this role earn between $15.67 and $20.38 per hour, depending on experience, location, and employer.

What is an internship numerical methods?

Internship numerical methods refer to internships focused on applying mathematical techniques and algorithms to solve real-world problems using numerical computations. These internships typically involve working with numerical analysis, modeling, simulation, and programming to analyze data or solve engineering and scientific problems. Interns may use tools like MATLAB, Python, or specialized software to implement and test numerical algorithms under the guidance of professionals. Such internships are valuable for students in mathematics, engineering, physics, or computer science, offering practical experience in computational problem-solving.

What types of projects can an intern expect to work on during a Numerical Methods internship?

As a Numerical Methods intern, you can expect to work on projects involving the development, implementation, and testing of algorithms for solving mathematical problems—such as differential equations, optimization, or data analysis tasks. You may collaborate with engineers or researchers to improve computational models, validate results, or optimize code for efficiency. These projects often require a mix of programming (commonly in Python, MATLAB, or C++), mathematical analysis, and teamwork. This hands-on experience is valuable for building problem-solving skills and gaining exposure to real-world applications of numerical techniques.

What are the key skills and qualifications needed to thrive as an intern in Numerical Methods, and why are they important?

To thrive as an intern in Numerical Methods, you need a solid understanding of mathematics, computational modeling, and problem-solving, typically supported by coursework in applied mathematics, engineering, or computer science. Familiarity with programming languages like Python or MATLAB and exposure to numerical analysis software are often expected. Strong analytical thinking, attention to detail, and effective communication help interns interpret results and collaborate with team members. These skills are crucial for accurately solving complex numerical problems and contributing to research or engineering projects.

What is the difference between Internship Numerical Methods vs Data Analyst?

AspectInternship Numerical MethodsData Analyst
Required CredentialsBasic knowledge of mathematics, programming, and numerical algorithmsBachelor's degree in statistics, mathematics, or related field
Work EnvironmentInternship setting, often in research or technical teamsOffice environment, working with data sets and reporting tools
Employer & Industry UsageResearch institutions, engineering firms, tech companiesBusiness, finance, healthcare, marketing sectors
Search & Comparison IntentUnderstanding entry-level roles in numerical computationExploring data analysis careers and skills

Internship Numerical Methods focuses on applying mathematical and computational techniques to solve problems, often in research or technical settings. Data Analyst roles involve interpreting data, creating reports, and supporting decision-making in various industries. While both require analytical skills, internships emphasize learning and applying numerical algorithms, whereas data analysts focus on data interpretation and visualization.

What are popular job titles related to Internship Numerical Methods jobs in Boston, MA?

For Internship Numerical Methods jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Internship Numerical Methods jobs in Boston, MA look for?

The top searched job categories for Internship Numerical Methods jobs in Boston, MA are:

Internship Numerical Methods jobs near you
Infographic showing various Internship Numerical Methods job openings in Boston, MA as of July 2026, with employment types broken down into 2% Internship, 74% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $39,688 per year, or $19.1 per hour.

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA • On-site

Full-time

Re-posted 3 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)