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Quantitative Trader Intern

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WallStreetQuants logoWallstreetquants · New York, NY
Full-timeOn-siteToday
PythonSQLMachine LearningiOS
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About the role

An NYC based proprietary trading firm is seeking a motivated Quantitative Trader Intern to join our trading team. 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 alongside experienced traders, researchers, and engineers to analyze market behavior, develop trading insights, and support the execution and improvement of systematic trading strategies. This role offers hands-on exposure to real-time markets, quantitative research, and the trading decision process. Responsibilities Analyze financial market data to identify patterns, inefficiencies, and trading opportunities. Assist in the development, testing, and refinement of quantitative trading strategies. Build tools and dashboards to monitor market activity, strategy performance, and trading signals. Conduct statistical analysis and backtesting using historical data. Collaborate with traders, researchers, and engineers to improve trading models and workflows. Monitor live markets and help evaluate risk, execution quality, and strategy behavior. Present research findings and trading insights to the broader team. Qualifications Currently pursuing a Bachelor's, Master's, or PhD degree in Mathematics, Statistics, Computer Science, Engineering, Physics, Economics, Finance, or a related quantitative field. Strong analytical and problem-solving skills. Solid understanding of probability, statistics, and mathematical modeling. Programming experience in Python, R, or a similar language. Interest in financial markets, trading, game theory, or competitive problem-solving. Ability to work well in a fast-paced, collaborative environment. Strong attention to detail and intellectual curiosity. Preferred Qualifications Experience with data analysis, machine learning, optimization, or time-series modeling. Prior exposure to trading, investing, market microstructure, or financial derivatives. Experience with pandas, NumPy, SQL, or other data analysis tools. Participation in math competitions, programming contests, poker, chess, sports betting, or other strategy-based competitions. Ability to communicate complex ideas clearly and concisely. What You'll Gain Hands-on experience working with real-world financial market data. Exposure to systematic trading, risk management, and strategy development. Mentorship from experienced quantitative traders and researchers. The opportunity to contribute to projects with direct trading impact. A deeper understanding of how quantitative analysis is applied in live markets.


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