Equity Volatility Quant Research Intern - Summer 2027

Walleye Capital Full Time; Miami (FL); On-site; USD 203,000 - 243,000; Full time

Job summary

Walleye Capital invites applications for an Equity Volatility Quant Researcher Intern for Summer 2027 in Miami. The 10-week program offers hands-on exposure to end-to-end research and trading workflows in a leading multi-strategy firm.

Ideal candidates are pursuing a quantitative undergraduate or non-MBA degree with Python and data experience, and a strong foundation in probability, statistics, time-series analysis, and ML. Collaboration with PMs and researchers is emphasized.

Qualifications

• Pursuing an undergraduate or non-MBA quantitative degree with expected graduation between Dec 2027 and Jun 2028.
• Strong programming skills in Python and experience with large datasets, APIs, or databases.
• Strong knowledge of probability and statistics, including time-series analysis, ML, and optimization.
• Self-starter who can work independently and in a team.
• Genuine interest in financial markets, risk taking, and technology in data-rich environments.

Responsibilities

• Build foundation in options markets from academic and practitioner perspectives.
• Monitor macro developments and market headlines and assess their impact on trading decisions and risk.
• Collaborate with portfolio managers and quantitative researchers in volatility strategies.
• Conduct quantitative research tasks using large-scale volatility datasets.
• Enhance research infrastructure and tools for trading and risk management, leveraging AI.

Skills

Python

Large datasets

APIs & databases

Time-series analysis

Machine learning

Education

Undergraduate/Non-MBA quantitative degree

Tools

Pandas

NumPy

SQL

Job description

Walleye Capital invites applications for an Equity Volatility Quant Researcher Intern for Summer 2027 in Miami. The 10-week program offers hands-on exposure to end-to-end research and trading workflows in a leading multi-strategy firm.

Ideal candidates are pursuing a quantitative undergraduate or non-MBA degree with Python and data experience, and a strong foundation in probability, statistics, time-series analysis, and ML. Collaboration with PMs and researchers is emphasized.