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Quant Intern Jobs in Randolph, MA (NOW HIRING)

DataRobot

Agentic AI Intern

Boston, MA · Remote

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 ...

DataRobot

Agentic AI Intern

Boston, MA · Remote

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 ...

DataRobot, Inc.

Agentic AI Intern

Boston, MA · On-site

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 ...

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Quant Intern information

Is it hard to get a quant internship?

Securing a quant internship is competitive due to high demand and rigorous requirements. Candidates typically need strong quantitative skills, programming knowledge in languages like Python or C++, and relevant academic backgrounds such as mathematics, finance, or engineering. Strong analytical ability and experience with data analysis tools can improve chances of acceptance.

What skills and qualifications are needed to thrive as a quant intern?

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.

How much do quant interns get paid?

Quant interns typically earn between $20 and $40 per hour, with total summer internship stipends ranging from $5,000 to $15,000 depending on the firm and location. Compensation often includes exposure to programming languages like Python or C++ and financial modeling tools. Internships usually last 10 to 12 weeks and may offer additional benefits or bonuses.

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 cities near Randolph, MA are hiring for Quant Intern jobs? Cities near Randolph, MA with the most Quant Intern job openings:
Quant Intern jobs near you

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA • On-site

Full-time

Re-posted 27 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)