Quantitative Trading Intern - Summer 2027 (DV Equities)
As a Quantitative Trading Intern, you will work with our DV Equities trading teams and gain exposure to our proprietary methodologies and trading systems. You will build and backtest quantitative trading models, analyze high-frequency market data to identify predictive signals, and collaborate with traders and researchers to refine systematic strategies. You will also monitor daily trading processes, analyze and resolve discrepancies in trade positions and P&L attribution, and identify new market opportunities through data-driven research.
Trading interns work in a relatively flat organizational structure and are mentored by senior traders and quantitative researchers.
Responsibilities:
Build, backtest, and refine quantitative trading models using historical market and orderbook data
Analyze large datasets to identify patterns, inefficiencies, and alpha signals for systematic strategy development
Monitor real-time trading positions and market conditions, assisting traders with risk management and parameter adjustments
Collaborate with quantitative researchers and software developers to implement strategy prototypes into the firm's low-latency execution infrastructure
Oversee and improve daily trading processes as needed
Analyze and resolve discrepancies in trade positions and P&L attribution
Identify new market opportunities through data-driven research
Prepare clear reports and presentations summarizing research findings, trading performance, and recommendations
Requirements:
Pursuing a Bachelor's, Master's, or PhD in a quantitative field (Mathematics, Statistics, Computer Science, Physics, Engineering, Economics, or related), with an expected graduation by Summer 2027
Strong interest in quantitative trading, systematic strategy development, and financial markets
Strong proficiency in Python; experience with C++ is highly preferred
Familiarity with probability, statistics, and time-series analysis
Prior exposure to financial markets, trading, or quantitative research (through internships, academic projects, or competitions) is highly preferred
Proficiency with Excel and data analysis tools
Strong work ethic and ability to learn quickly in a fast-paced, high-pressure environment
Excellent communication and collaboration skills