Quantitative Developer

About the role

You’ll sit directly inside the investment process—not supporting it from a distance or waiting for requirements to arrive through several layers of stakeholders. You’ll work alongside quantitative researchers, portfolio managers, and other engineers on systems used to research, evaluate, and implement live investment strategies.

Responsibilities

• Building research and analytical tools used across fundamental and systematic equities teams
• Developing systems supporting signal research, portfolio construction, optimization, risk, and execution
• Turning research ideas into production-grade tools that are scalable, measurable, and reliable
• Building backtesting, simulation, and portfolio analytics frameworks
• Working with market, fundamental, alternative, and portfolio datasets
• Improving how investment ideas move from research into live portfolios
• Developing tools for risk analysis, hedging, performance attribution, and post-trade evaluation
• Owning systems through design, implementation, deployment, and continued improvement

You’ll be measured by whether the systems you build improve the research process, make investment decisions better, or allow teams to operate faster and more effectively. When a problem matters, you’ll be expected to understand it properly and take ownership of the outcome.

Requirements

• Strong in Python and care about writing correct, durable software
• Enjoy problems that sit between engineering, quantitative research, and decision-making
• Want to understand why a system is being built, not simply what the requirements say
• Interested in portfolio construction, optimization, risk, execution, or systematic research
• Comfortable working with complex datasets and ambiguous problems
• Value short feedback loops and proximity to the end user
• Early in your career but already thoughtful about where you invest your time

Experience in finance is helpful but not the only filter. Strong candidates may come from technology companies, research organizations, quantitative firms, or other environments where engineering quality and analytical thinking genuinely matter. Trajectory, judgement, and ownership carry more weight than having the perfect background.

Trade-offs

This environment won’t suit everyone. The expectations are high, your work is visible, and you’ll receive direct feedback—the standard will continue moving as you improve. There’s limited hand-holding, and you won’t always be given a perfectly written specification.

In return: decisions are made quickly, strong ideas are taken seriously, engineers have genuine ownership, and you’ll work closely with experienced investors and researchers. Progression is driven by contribution rather than tenure. People who perform well here don’t wait for someone to decide they’re ready—their scope grows because they repeatedly prove they can handle more.

Location: New York / London | Experience: 1–10 years