Quantitative Developer - New Grad

Metabit; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Metabit is seeking a Quantitative Developer for its Execution Algo team to shape the core trading engine. You will translate research concepts into high-performance C++ and Python, build backtesting tools, and analyze live execution quality across global markets.

You'll collaborate with Quant Researchers, Core Engineers, and Production Trading Operations to optimize strategies, ensure reliability, and push the boundaries of market microstructure in a sophisticated trading environment.

Qualifications

• Degree in CS, Engineering, Math, Physics, or related quantitative field.
• Strong coding in Python and C++, with knowledge of data structures and algorithms.
• Solid background in probability, statistics, and data analysis.
• Interest in financial markets and market microstructure.
• Excellent collaboration across researchers, engineers, and traders.

Responsibilities

• Participate in the full lifecycle of quantitative strategy implementation, focusing on code optimization, deployment, order execution tracking, policy compliance, and risk control mechanisms.
• Develop and enhance strategy research tools on our in-house backtesting platform.
• Contribute to the development and maintenance of live trading processes, improving production quality and reliability.
• Collaborate with the engineering team to implement core components of distributed systems, data platforms, and trading infrastructure.

Skills

Python

C++

Data analysis

Probability

Statistics

Software design

Education

Bachelor's degree in CS/Engineering/Math/Physics

Tools

Backtesting Platform

Git

Linux

Job description

Position Overview

We are seeking a talented 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

We are seeking a talented 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 focus on execution logic, simulation tooling, and data analysis across global equity and futures markets. Working closely with senior members of the team, you will act as a core engine for implementation—translating research concepts into code, expanding our backtesting frameworks, and analyzing live execution quality. This position offers a direct path to mastering market microstructure and high-performance software development within a sophisticated trading environment.

Key Responsibilities

• Strategy Lifecycle Support: Participate in the full lifecycle of quantitative strategy implementation, focusing on code optimization, deployment, order execution tracking, policy compliance, and risk control mechanisms.
• Research Tooling & Backtesting: Work closely with the research team to develop and enhance strategy research tools on our in-house backtesting platform, tailoring them to their specific use cases.
• Live Operations & Reliability: Contribute to the development and maintenance of live trading processes, continuously improving the production quality and reliability of strategies through robust technical solutions.
• Infrastructure Integration: Collaborate with the engineering team to implement core components of our distributed systems, data platforms, and trading infrastructure, ensuring your code directly supports both research and live trading performance.
• Feature Iteration: Collaborate with senior developers to implement, test, and iterate on execution algorithms and trading features based on research models.

Required Qualifications & Skills

• Educational Background: Degree in Computer Science, Engineering, Mathematics, Physics, or a highly quantitative field.
• Strong Coding Fundamentals: Clean, proficient coding skills in Python (for data analysis and tooling) and C++ (for core systems logic). Solid understanding of data structures, algorithms, and software design principles.
• Quantitative Competency: Strong grounding in probability, statistics, and data analysis; comfortable working with large datasets and debugging complex log files.
• Eagerness to Learn: A deep, demonstrable interest in financial markets, electronic execution, and market microstructure.
• Collaborative Mindset: Excellent communication skills with the ability to working effectively across different disciplines (researchers, core engineers, and 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.