Quantitative Developer

• A degree in computer science with a quantitative focus (math, finance, etc.), or a quantitative degree with a strong computer science component \n

• 2+ years of relevant work experience \n

• A track record of strong academic or professional performance \n

• Solid analytical and problem-solving abilities \n

• Hands-on experience writing production-quality C++ for a data-driven or performance-sensitive business, ideally in trading or investment management \n

• Advanced C++ skills, including templates, the STL, move semantics, and memory management \n

• Experience with multithreading, concurrency, and performance profiling on Linux \n

• Strong grasp of object-oriented and generic programming, data structures, and numerical algorithms \n

• Working knowledge of probability and statistics, including regression and time-series methods \n

• Familiarity with Python is a plus, particularly for prototyping and integrating with research tooling \n

• A curious mindset and openness to learning new tools \n

• Interest in financial markets (no prior experience required), * Strong communication skills, including the ability to explain technical tradeoffs to researchers

We’re hiring Quantitative Developers to join our Research team. This role blurs the lines between research and development and lets you contribute on both fronts. The team is collaborative and data-focused: it generates investment ideas, translates them into trading signals, back-tests those signals, and builds return, risk, and cost forecasts that inform trading decisions. The team values a supportive, professional culture built on initiative and strong work ethic.

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The quantitative development function within Research builds the high-performance C++ libraries, simulation engines, and APIs that let the broader team generate, test, and deploy investment ideas faster.

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In this role, you’ll contribute to a next-generation research platform built on modern C++, distributed computing, and cloud technologies, working on core components where performance directly shapes how quickly the team can iterate.

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What You’ll Do

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Scope will expand as your skills and experience grow. Depending on your strengths, your day-to-day may include:

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1. Designing, writing, and maintaining modern C++ (17/20) code that powers research and production workflows \n

2. Building and optimizing core components of the research stack, including back-testing and simulation engines, signal libraries, and numerical toolkits \n

3. Profiling and tuning performance-critical code for latency, throughput, and memory efficiency (cache behavior, vectorization, multithreading) \n

4. Exposing C++ libraries to researchers through clean APIs and Python bindings (e.g. pybind11) \n

5. Running exploratory statistical analysis on large, complex datasets from structured and unstructured sources \n

6. Evaluating new libraries, compilers, and tooling through proof-of-concept work \n

7. Partnering with engineers to design high-volume data feeds from third-party vendors \n

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