PhD Quantitative Researcher Intern

Responsibilities

• Research, design, and test predictive signals, data sets, and systematic trading strategies
• Extract and analyze large datasets from structured and unstructured sources using advanced statistical methods
• Enhance research infrastructure and tools for trading, risk management, and attribution
• Develop machine learning models to predict patterns in asset returns, risks, and trading costs
• Design and implement scalable code across various stages of the investment process
• Work in Python and/or R to contribute to research tools and libraries
• Leverage AI tools including LLM-based analytical pipelines to enhance processes

Requirements

• Currently pursuing a PhD in computer science, engineering, statistics, operations research, mathematics, or a related field
• Expected graduation date between December 2027 and June 2028
• Strong programming skills in Python or R
• Experience working with large datasets, APIs, or databases
• Rigorous analytical thinking and statistical modeling abilities
• Familiarity with machine learning, optimization, or time-series analysis
• Interest in financial markets and systematic investing

About the Company

Walleye Capital is a ~$16 billion+ multi-strategy investment firm specializing in Quant, Fundamental Equities, and Volatility strategies. Its Quantic team is a highly successful quantitative investment business leveraging advanced statistical modeling to capitalize on global equities, options, and futures.