Quantitative Developer

The role

You will own the full research cycle — from raw market data to a statistically validated signal — and collaborate closely with our C++ engineers to translate prototypes into production strategies. The boundary between research and engineering is deliberately thin here; you are expected to write production-quality Python and be comfortable reading and contributing to the C++ codebase when necessary.

This is a senior individual-contributor role. There is no management track and no expectation of people management.

Responsibilities

• Identify, develop, and validate alpha signals using tick, order-book, and alternative data.
• Build and maintain a robust backtesting framework that accounts for transaction costs, slippage, and capacity constraints.
• Model spread dynamics, market impact, and adverse selection for market-making and stat-arb strategies.
• Perform live monitoring of deployed strategies; investigate P&L attribution and decay.
• Collaborate with C++ engineers to specify the interfaces and timing requirements for production implementations.
• Maintain a disciplined research log; all experiments are reproducible and documented.

Requirements

• PhD or equivalent research experience in mathematics, statistics, physics, computer science, or a related quantitative field.
• Expert-level Python; experience with NumPy, Pandas, Polars, or similar data-manipulation stacks.
• Strong grounding in statistics: time-series econometrics, hypothesis testing, Bayesian inference, or machine learning applied to financial data.
• Familiarity with equity and derivative market microstructure — order types, matching mechanics, clearing.
• Ability to write clean, testable code; research prototypes that become unmaintainable are a liability.
• Comfort working in a Linux environment; proficiency with git and command-line data tooling.

Nice to have

• Experience reading or writing C++ in a performance-sensitive context.
• Familiarity with FIX protocol or proprietary exchange binary protocols.
• Prior experience at a proprietary trading firm, hedge fund, or systematic asset manager.
• Publications in quantitative finance, machine learning, or applied statistics.