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Quantitative Trader

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Onsite

Quantitative Trader

Metabit Asset Management Pte. Ltd.

Quantitative Trader

Skills

PythonComplianceRisk Management

25 days ago

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Important information


Contract type:

Permanent

Location:

Singapore

Work mode:

Onsite

Published on:

26 September 2026

What they need


Job Responsibilities

Monitor

the operation of trading programs and respond promptly and accurately to various unexpected incidents.

Collaborate

with internal research teams and external dealers/brokers to ensure the smooth execution of the trading process.

Execute

trading orders in a timely and accurate manner, follow up on inquiries and trading workflows, and complete trading tasks with high quality and efficiency.

Monitor

macro events and market trends, providing risk alerts on critical market changes.

Propose

recommendations to improve the accuracy and efficiency of risk management systems, and collaborate with the engineering team to implement these enhancements.

Job Requirements

Bachelor’s degree or above in Finance or a related discipline; proficiency in computer programming (Python) is a strong plus.

Strong awareness of compliance and confidentiality, with a high sense of responsibility, resilience under pressure, and excellent multi-tasking abilities.

1 to 3 years of A-share trading experience at well-known domestic or international institutions is preferred.

Excellent English communication and presentation skills.

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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