Quantitative Developer – Execution

METABIT ASSET MANAGEMENT PTE. LTD.; Singapore; On-site; SGD 120,000 - 200,000; Full time

Job summary

METABIT ASSET MANAGEMENT PTE. LTD. seeks a highly capable developer to drive full lifecycle quantitative strategy projects. You will research, optimize, deploy, and monitor live trading systems with strong focus on low-latency C++ and data-driven Python tooling.

You will collaborate with engineering and research to build robust backtesting tools and scalable data platforms, ensuring efficient execution for equity and futures markets.

Qualifications

• Proficient in Linux environments and production-level C++ for low-latency components.
• Python used for data analysis, rapid prototyping, and framework development.
• Solid understanding of equity and futures markets, market microstructure, and execution logic.
• Experience contributing to or designing complex frameworks (backtesters, data pipelines, or analytics engines).
• Comfortable with statistics, data analysis, and evaluating execution signals and performance metrics.

Responsibilities

• Participate in full lifecycle of quantitative strategy implementation including research, code optimization, deployment, and risk control.
• Design and develop strategy research tools on in-house backtesting platform for specific use cases.
• Own development and maintenance of live trading processes and improve production quality and reliability.
• Collaborate with engineering to shape core components of distributed systems, data platforms, and trading infrastructure.
• Partner with research to iterate on execution features and translate models into high-performance, low-latency code across markets.

Skills

Linux

C++ (modern)

Python

Low-latency

Data analysis

Equity & Futures

System design

Statistics

Tools

Backtesting Platform

FIX protocol

Exchange APIs

Job description

Key Responsibilities

• 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.
• 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.
• 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.
• 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.
• 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

• Strong Programming Foundations:Proficient in Linux environments, Production-level experience inC++(modern standards) for low-latency components andPythonfor data analysis, rapid prototyping, and framework development.
• Domain Expertise:Solid understanding ofequity and futures markets, including market microstructure, order book dynamics, and electronic execution logic.
• System Design & Architecture:Experience contributing to or designing complex frameworks (e.g., backtesters, data pipelines, simulation environments, or analytics engines).
• Mathematical/Quantitative Literacy:Comfortable with statistics, data analysis, and evaluating the mathematical logic behind execution signals and performance metrics.
• Communication & Collaboration:Exceptional ability to translate concepts between highly academic researchers, strict system engineers, and fast-paced production traders.

Preferred/Nice-to-Have

• 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.