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Quant Intern Jobs in Boston, MA (NOW HIRING)

Each AI Native Intern is embedded in a real team, working on real problems, and is expected to ... quantitative field * Working proficiency in Python (pandas, numpy) and comfort with data ...

Each AI Native Intern is embedded in a real team, working on real problems, and is expected to ... quantitative field * Working proficiency in Python (pandas, numpy) and comfort with data ...

Each AI Native Intern is embedded in a real team, working on real problems, and is expected to ... quantitative field * Working proficiency in Python (pandas, numpy) and comfort with data ...

... related quantitative field with strong foundations in linear algebra and 3D geometry. * Deep ... Intern Benefits & Perks: * Flexible Out of Office Plan - take time when you need it * Salaried bi ...

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Quant Intern information

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$52

$133

How much do quant intern jobs pay per hour?

As of Jul 29, 2026, the average hourly pay for quant intern in Boston, MA is $52.73, according to ZipRecruiter salary data. Most workers in this role earn between $16.21 and $82.35 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Quant Intern position, and why are they important?

To thrive as a Quant Intern, you need a solid background in mathematics, statistics, computer science, or a related field, often supported by coursework in probability, calculus, and linear algebra. Proficiency with programming languages such as Python, R, or MATLAB, and familiarity with data analysis tools and version control systems, are commonly required. Exceptional problem-solving skills, attention to detail, and the ability to communicate complex concepts clearly are vital soft skills for this role. These skills enable interns to analyze large datasets, develop quantitative models, and contribute effectively to fast-paced, collaborative finance or technology teams.

What does a Quant Intern do?

A Quant Intern supports quantitative researchers and traders by analyzing financial data, developing mathematical models, and coding algorithms to improve trading strategies. Interns typically use programming languages like Python and C++ and work with large data sets to identify patterns and optimize risk management. The role requires strong analytical skills, proficiency in statistics, and a solid understanding of financial markets.

What kinds of projects or tasks can I expect to work on as a Quant Intern?

As a Quant Intern, you will typically work on projects involving data analysis, building and testing quantitative models, and assisting in the implementation of trading algorithms or risk management tools. You may be expected to clean and analyze large datasets, backtest strategies, and prepare summaries or visualizations of your findings for your team. Interns often collaborate closely with experienced quantitative analysts and traders, receiving mentorship and guidance throughout the process. This hands-on work provides valuable exposure to the workflow and challenges of quantitative finance, allowing you to build practical skills and a strong foundation for a future career in the field.

What are the most commonly searched types of Quant jobs in Boston, MA? The most popular types of Quant jobs in Boston, MA are:
What cities near Boston, MA are hiring for Quant Intern jobs? Cities near Boston, MA with the most Quant Intern job openings:
Infographic showing various Quant Intern job openings in Boston, MA as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $109,688 per year, or $52.7 per hour.

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA โ€ข On-site

Full-time

Re-posted 22 days ago


Job description

Ph.D. Graduate Intern โ€“ 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 applyโ€”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 approachesย 
  • Analyze large, high-dimensional financial datasets to uncover structure, dependencies, and sources of riskย 
  • Design and implement analytical tools and pipelines using Python and SQLย 
  • Contribute to model validation, backtesting, and performance evaluationย 
  • Collaborate with risk, engineering, and data teams to improve model scalability and data infrastructureย 
  • Communicate complex quantitative insights through clear visualizations and technical summariesย 
  • Apply advanced methodologies from your discipline (e.g., stochastic modeling, optimization, machine learning, or geometric/topological approaches) to improve risk analyticsย 
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)ย 
  • Strong foundation in probability, statistics, and numerical methodsย 
  • Proficiency in Python (NumPy, pandas, or similar) and/or SQLย 
  • Experience working with large datasets and implementing quantitative modelsย 
  • Ability to think rigorously about complex systems and translate theory into practical solutionsย 
Preferred Qualifications
  • Familiarity with quantitative finance concepts (e.g., portfolio theory, factor models, volatility modeling, Value-at-Risk)ย 
  • Experience with scientific computing, optimization, or machine learningย 
  • Background or research in cross-disciplinary areas such as:ย 
    • Statistical physics, complex systems, or network theoryย 
    • Applied or computational mathematicsย 
    • Machine learning or probabilistic modelingย 
    • Quantum computing or advanced optimization techniquesย 
    • Topological data analysis or geometric data methodsย 
  • Prior research, publications, or project work demonstrating advanced quantitative modelingย 
What Youโ€™ll Gain
  • Exposure to real-world portfolio risk problems at the intersection of finance and advanced analyticsย 
  • Opportunity to apply cutting-edge academic methods in a production environmentย 
  • Collaboration with a highly quantitative, cross-disciplinary teamย 
  • Experience working with large-scale financial data and modern analytics infrastructureย 
  • Mentorship and potential pathway to full-time quantitative rolesย 
Duration & Compensation
  • Internship: Summer 2026, with potential to extendย 
  • Paid internship (competitive, based on experience and location)
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