Quantitative Researcher - Summer Internship at WallStreetQuants

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

25 Sep, 26

Salary

0.0

Posted On

27 Jun, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Statistical Analysis, Data Analysis, Financial Modeling, Backtesting, Probability, Linear Algebra, Optimization, Pandas, NumPy, Matplotlib, Scikit-learn, SQL, Machine Learning, Econometrics, Time Series Analysis

Industry

Education

Description

About the Internship A New York based Hedge Fund is seeking an Undergraduate Quantitative Research Intern to join their quantitative research team. This internship is designed for undergraduate students interested in applying mathematics, statistics, programming, and data analysis to financial markets. You will work alongside experienced researchers and traders to explore market data, test research ideas, and help evaluate systematic trading strategies. This is a hands-on opportunity to gain exposure to quantitative finance in a collaborative and intellectually challenging environment. Responsibilities Analyze financial and market datasets using statistical methods. Assist with research on systematic trading strategies. Clean, organize, and validate large datasets. Build simple models and backtests under researcher supervision. Write Python code for data analysis, visualization, and research workflows. Summarize findings clearly through charts, reports, or presentations. Collaborate with researchers, traders, and engineers on research projects. Learn how quantitative research ideas are developed, tested, and evaluated. Qualifications Currently pursuing a bachelor’s degree in Mathematics, Statistics, Computer Science, Engineering, Physics, Economics, Finance, or a related quantitative field. Expected graduation date of 2028 or 2029. Strong academic performance in quantitative coursework. Programming experience in Python. Familiarity with probability, statistics, linear algebra, or optimization. Interest in financial markets, trading, investing, or data-driven decision-making. Strong problem-solving skills and attention to detail. Ability to communicate technical ideas clearly. Preferred Qualifications Experience with pandas, NumPy, matplotlib, scikit-learn, or similar tools. Coursework or projects involving data analysis, machine learning, econometrics, or time series. Familiarity with SQL or databases. Participation in math, programming, trading, data science, or research competitions. Prior internship, academic research, or independent project involving quantitative analysis. What You’ll Gain Exposure to real-world quantitative research and systematic trading. Mentorship from experienced researchers and traders. Practical experience working with financial data. Opportunity to contribute to meaningful research projects. A deeper understanding of careers in quantitative finance.

Responsibilities

The intern will analyze financial datasets and assist in the research and evaluation of systematic trading strategies. Responsibilities include cleaning large datasets, building models, and writing Python code for research workflows.