Quant Researchers & Strategists

TED Optimus Sdn; Kuala Lumpur; On-site; MYR 60,000 - 90,000; Full time

Job summary

TED Optimus Sdn in Kuala Lumpur is seeking a quantitative professional to develop, back-test, and deploy systematic trading strategies based on AI-generated signals. Candidates should have a strong quantitative background, deep understanding of market microstructures, and a proven risk management track record.

This role involves constructing portfolios, conducting research to improve execution, and continuously monitoring live performance. Proficiency in Python and familiarity with Git are essential.

Qualifications

• Strong quantitative background required.
• Deep understanding of market microstructure and systematic trading.
• Proven track record of disciplined risk management.
• Proficiency in Python and back-testing frameworks.
• Comfortable using Git.

Responsibilities

• Develop, back-test and deploy systematic trading strategies.
• Construct and optimize portfolios with disciplined position sizing.
• Research market microstructure to improve execution.
• Subject strategies to testing before deployment.
• Monitor live performance and refine strategies.

Skills

Quantitative background (statistics, mathematics, finance)

Understanding of market microstructure

Risk management

Python proficiency

Experience with back-testing frameworks

Git

Job description

Translate AI-generated signals into optimal portfolios. If you have a deep understanding of market microstructures and a proven track record of disciplined risk management, your ultimate sandbox is here.

At Axiom Quant you will turn research and machine-generated signals into live, risk-controlled strategies tested against more than a decade of market cycles.

Responsibilities

• Develop, back-test and deploy systematic trading strategies built on AI-generated signals
• Construct and optimize portfolios with disciplined position sizing and risk controls
• Research market microstructure to improve execution and reduce trading costs
• Subject strategies to blind testing, stress testing and tail-risk scenarios before deployment
• Monitor live performance and continuously refine strategies and risk limits

Requirements

• Strong quantitative background (statistics, mathematics, finance or related)
• Deep understanding of market microstructure and systematic trading
• Proven track record of disciplined risk management
• Proficiency in Python and back-testing frameworks
• Comfortable using Git

Qualities

• Respects the market - puts risk control above potential returns
• Disciplined, detail-oriented and intellectually honest about results
• Creative in finding edge, rigorous in validating it
• Strong sense of ownership over strategies and their outcomes