Graduate Quantitative Developer
DeepFin Research
New York, NY0–3 yrs3h agovia LinkedIn
This job at a glance
- Who can apply
- New grads and up to 3 years · Bachelor's degree
- Must know
- C++Data structures & algorithms
- Nice to have
- PythonPandasNumPy
- Work
- On-site in New York
- Pay
- Not stated by the employer.
- Skill demand
- Python65%C++40%Data structures & algorithms35%of 43 similar entry-level jobs posted in the US this week
- Listed
- Oct 29, 2026 · still open
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About the Role
DeepFin Research is hiring a junior Quantitative Developer to productionise research into robust, high-performance trading systems. You will work closely with Quant Researchers and senior engineers to convert Python research code into production C++, build and optimise backtesting/simulation infrastructure, and support strategy development using L3 market data across multiple venues. This is a hands-on, engineering-heavy role where you will own components end-to-end and contribute directly to research velocity and trading PnL.
Key Responsibilities
- Productionise research models into C++: translate Python prototypes into efficient, maintainable C++ production code.
- Backtesting & simulation: build and improve simulation systems that reflect real market mechanics (order book, fills, cancels, exchange rules).
- L3 market data handling: ingest and process high-volume tick/order-level feeds; create reliable feature pipelines from raw exchange data.
- Performance optimisation: improve latency and throughput of backtests/sims (profiling, memory optimisation, data structures, parallelism where appropriate).
- Research support tooling: create utilities for data inspection, experiment tracking, run orchestration, and post-trade analytics in Python.
- Debugging & correctness: investigate mismatches between simulation and production behaviour; diagnose edge cases and implement fixes with strong test coverage.
- Cross-team collaboration: work daily with researchers and infra/exec engineers to ship improvements from idea → test → production.
Requirements & Tech Stack
- Education: Bachelor's or Master's from a top university in Computer Science, Engineering, Math, Physics, or similar.
- Strong working knowledge of C++ (memory, ownership, STL, performance-aware coding).
- Experience: demonstrable evidence of hands-on systems work in C++ handling large-scale data (internships, research labs, competitive projects, open-source).
- Comfortable with Python for analysis, tooling, and debugging (pandas, numpy, Jupyter a plus).
- Exposure to quantitative finance, eg through internships/university societies, including market microstructure and L3/order book data.
- Clear "builder mindset": you like owning problems end-to-end, shipping incrementally, and iterating quickly.