At a glanceSummarised by Seekless from the posting.
Must have7
Proficient in Linux environments
Production-level experience in C++ (modern standards) for low-latency components
Production-level experience in Python for data analysis, rapid prototyping, and framework development
Solid understanding of equity and futures markets, including market microstructure, order book dynamics, and electronic execution logic
Experience contributing to or designing complex frameworks (e.g., backtesters, data pipelines, simulation environments, or analytics engines)
Comfortable with statistics, data analysis, and evaluating the mathematical logic behind execution signals and performance metrics
Exceptional ability to translate concepts between highly academic researchers, strict system engineers, and fast-paced production traders
Nice to have6
Outstanding performance in competitive programming contests such as NOI or ICPC
Experience with distributed systems, high-performance computing (HPC), or handling large-scale tick data
Familiarity with connectivity protocols (e.g., FIX, native exchange APIs)
Publications in top-tier CS or Statistics journals/conferences
Award-winning participant in Kaggle machine learning competitions
Internship or work experience in proprietary trading firms, hedge funds, or leading tech companies
Skills
C++
Python
Linux
FIX
Kaggle
Position Overview
We are seeking a highly skilled Quantitative Developer to join our Execution Algo team. This team plays a critical, central role in our trading operation, sitting directly at the intersection of Quantitative Research, Core Engineering, and Production Trading Operations.
In this role, you will be the bridge that transforms alpha signals and execution research into robust, live trading strategies. You will collaborate closely with researchers to build tailormade strategy research tools, work alongside engineering to shape core system components, and take full ownership of production trading processes. If you thrive on writing high-performance code while deeply understanding market microstructure and full-lifecycle algorithmic execution, this role is for you.
Key Responsibilities
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Full-Lifecycle Implementation: Participate in the full lifecycle of quantitative strategy implementation, including research, code optimization and deployment, order execution, policy compliance, and risk control.
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Research Tooling & Backtesting: Work closely with the research team to design and develop strategy research tools on our in-house backtesting platform, tailored to their specific use cases.
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Production Ownership: Take ownership of the development and maintenance of live trading processes, continuously improving the production quality and reliability of strategies through robust technical solutions.
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Infrastructure Collaboration: Collaborate with the engineering team to shape and implement core components of our distributed systems, data platforms, and trading infrastructure—your contributions will directly impact both research and live trading performance.
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Algo Optimization: Partner with the research team to iterate on execution features, translating mathematical models and signals into high-performance, low-latency code across global equity and futures markets.
Required Qualifications & Skills
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Strong Programming Foundations: Proficient in Linux environments, Production-level experience in C++ (modern standards) for low-latency components and Python for data analysis, rapid prototyping, and framework development.
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Domain Expertise: Solid understanding of equity and futures markets, including market microstructure, order book dynamics, and electronic execution logic.
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System Design & Architecture: Experience contributing to or designing complex frameworks (e.g., backtesters, data pipelines, simulation environments, or analytics engines).
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Mathematical/Quantitative Literacy: Comfortable with statistics, data analysis, and evaluating the mathematical logic behind execution signals and performance metrics.
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Communication & Collaboration: Exceptional ability to translate concepts between highly academic researchers, strict system engineers, and fast-paced production traders.
Preferred/Nice-to-Have
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Outstanding performance in competitive programming contests such as NOI or ICPC.
•
Experience with distributed systems, high-performance computing (HPC), or handling large-scale tick data.
•
Familiarity with connectivity protocols (e.g., FIX, native exchange APIs).
•
Publications in top-tier CS or Statistics journals/conferences.
•
Award-winning participant in Kaggle machine learning competitions.
•
Internship or work experience in proprietary trading firms, hedge funds, or leading tech companies.