Quantitative Trader

Firm Overview

Walleye Capital is a $17 billion+ multi-strategy investment firm headquartered in New York City, with over 400 employees across five main offices. Founded in 2005 as an options market maker, we have organically grown into a global investment firm specializing in Volatility, Fundamental Equities, and Quant strategies.

At Walleye, we continuously innovate by focusing on three core principles: approach, platform, and people. Our approach is to allocate risk capital where we believe there is not only a compelling opportunity, but also a clear ability to define our tangible edge.

We seek to leverage the mathematical benefits of diversification while utilizing sophisticated infrastructure, technology, and our balance sheet to do so in a structurally advantageous way. Our platform, developed over two decades, is central to our operations, evolving alongside business complexities and technological advancements to support our team's success.

Our people are our greatest asset, and we've cultivated an environment that attracts top talent by balancing autonomy with collaboration, and intelligence with integrity.

Position Overview

Walleye Capital is seeking a Quantitative Trader to join an Index Volatility team in New York. This role works directly alongside a Volatility Portfolio Manager in an apprenticeship-style seat, with close partnership across Quantitative Research and Technology teams to research, develop, and automate alpha-generating trading strategies. The ideal candidate will have strong statistical, analytical, and modeling skills, a passion for systematic investing, and interest in developing discretionary trading judgement alongside quantitative research.

Responsibilities

• Work directly with portfolio manager to research, design, and automate alpha-generating strategies across volatility markets
• Manipulate proprietary and public data to build custom datasets for use in research, signal development, and daily trading
• Build predictive models of volatility surfaces and asset prices across short, medium, and long-term horizons using regression and machine learning techniques
• Partner with portfolio manager on live trading, risk, and positioning decisions, developing discretionary judgement alongside systematic research
• Assume increasing autonomy over time, with a path to operating a secondary book and direct risk-taking responsibility

Qualifications

• Proficiency in statistical analysis and modeling of time series financial data in Python is required
• Solid understanding of options and volatility concepts, including pricing, greeks, and volatility surface dynamics, is required
• Experience performing quantitative research or trading at a leading firm is preferred
• Strong communication skills, such as ability to clarify task requirements, communicate research findings, and propose solutions to challenges, are required
• Demonstrated interest in decision-making under uncertainty, whether through trading, competitive games, or comparable experience, is preferred

Base salary

$200,000 plus a competitive bonus and comprehensive benefits package.