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Quantitative Finance Intern Jobs (NOW HIRING)

WallStreetQuants

Quantitative Developer Intern

New York, NY · On-site

$21 - $27.50/hr

As a Quantitative Developer Intern, you will work closely with quantitative researchers, traders ... Interest in financial markets, trading systems, quantitative research, or data-driven decision ...

WallStreetQuants

Quantitative Developer Intern

New York, NY · On-site

$21 - $27.50/hr

As a Quantitative Developer Intern, you will work closely with quantitative researchers, traders ... Interest in financial markets, trading systems, quantitative research, or data-driven decision ...

New

WallStreetQuants

Quantitative Trader Intern

New York, NY · On-site

This internship is designed for students who are passionate about financial markets, data analysis, probability, and decision-making under uncertainty. As a Quantitative Trader Intern, you will work ...

New

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Quantitative Finance Intern information

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How much do quantitative finance intern jobs pay per hour?

As of Jun 30, 2026, the average hourly pay for quantitative finance intern in the United States is $19.86, according to ZipRecruiter salary data. Most workers in this role earn between $17.07 and $22.36 per hour, depending on experience, location, and employer.

What does a Quantitative Finance Intern do?

A Quantitative Finance Intern works on developing and implementing mathematical models to analyze financial data, assess risk, and support trading or investment strategies. They use programming languages like Python, R, or C++ to process large datasets and apply statistical or machine learning techniques. Interns often collaborate with traders, quantitative analysts, and software engineers to optimize financial models and improve decision-making. This role provides hands-on experience in quantitative research, algorithmic trading, or risk management within financial institutions.

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

To thrive as a Quantitative Finance Intern, you need strong skills in mathematics, statistics, data analysis, and a background in finance, economics, or a related quantitative field. Proficiency with programming languages such as Python, R, or MATLAB, along with familiarity with financial modeling tools and Excel, is typically required. Excellent problem-solving abilities, attention to detail, and communication skills help you collaborate effectively within dynamic teams. These competencies are crucial for analyzing complex financial data and contributing meaningful insights in fast-paced finance environments.

What kinds of projects or tasks do Quantitative Finance Interns typically work on during their internship?

Quantitative Finance Interns often work on projects involving data analysis, financial modeling, and the development or back-testing of trading strategies under the supervision of senior analysts or portfolio managers. Typical tasks may include manipulating large datasets, applying statistical or mathematical models, coding algorithms, and preparing presentations or reports for stakeholders. Interns frequently collaborate with team members across research, trading, and risk management divisions, gaining exposure to real-world financial problem-solving. This role offers a hands-on learning environment that helps build practical skills and can open the door to full-time opportunities within the firm.

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Quantitative Finance Intern jobs near you
Infographic showing various Quantitative Finance Intern job openings in the United States as of June 2026, with employment types broken down into 66% Full Time, 27% Part Time, 5% Temporary, and 2% Contract. Highlights an 95% Physical, 2% Hybrid, and 3% Remote job distribution, with an average salary of $41,299 per year, or $19.9 per hour.

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA • On-site

Full-time

Posted 23 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)