- Outram Central Region (Singapore) Singapore
Metabit Asset Management Pte. Ltd. Hiring! Full Time Quantitative Developer – Execution in Central Region (Singapore), Earn up to SGD 20,000 - Ricebowl
Quantitative Developer – Execution
Metabit Asset Management Pte. Ltd.
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Job Description
Responsibilities
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 in
C++
(modern standards) for low-latency components and
Python
for data analysis, rapid prototyping, and framework development.
Domain Expertise:
Solid understanding of
equity 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.
We are dedicated to merging the precision of mathematics with the innovation of computer science, leveraging advanced artificial intelligence (AI) and machine learning (ML) to drive investment decisions and strategy development.Our name, "Metabit", combines "Meta" - referring to metadata in data science - and "bit", the fundamental unit of information in computing, symbolizing our approach of seamlessly integrating mathematics and computer science. Our competitive edge lies in continuously optimizing machine learning algorithms and effectively applying them to financial datasets characterized by extremely low signal-to-noise ratios, thereby delivering sustainable returns for our investors.Founded by industry leaders with academic backgrounds from world-renowned institutions such as Stanford University and Carnegie Mellon University, and professional experience at leading technology companies including Meta and Google, Metabit benefits from a strong foundation in both theoretical research and practical application. This expertise shapes our approach to tackling complex financial problems with innovative, data-driven solutions.
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 in
C++
(modern standards) for low-latency components and
Python
for data analysis, rapid prototyping, and framework development.
Domain Expertise:
Solid understanding of
equity 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.
We are dedicated to merging the precision of mathematics with the innovation of computer science, leveraging advanced artificial intelligence (AI) and machine learning (ML) to drive investment decisions and strategy development.Our name, "Metabit", combines "Meta" - referring to metadata in data science - and "bit", the fundamental unit of information in computing, symbolizing our approach of seamlessly integrating mathematics and computer science. Our competitive edge lies in continuously optimizing machine learning algorithms and effectively applying them to financial datasets characterized by extremely low signal-to-noise ratios, thereby delivering sustainable returns for our investors.Founded by industry leaders with academic backgrounds from world-renowned institutions such as Stanford University and Carnegie Mellon University, and professional experience at leading technology companies including Meta and Google, Metabit benefits from a strong foundation in both theoretical research and practical application. This expertise shapes our approach to tackling complex financial problems with innovative, data-driven solutions.
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