Quantitative Researcher

Anson McCade; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

A leading global hedge fund in Singapore seeks an experienced Quantitative Researcher to develop systematic equities strategies emphasizing statistical arbitrage. The ideal candidate has a strong technical foundation, 3+ years of relevant experience, and proficiency in Python and machine learning techniques. This position offers competitive compensation and a collaborative, research-driven environment.

Benefits

Competitive compensation package

Exposure to leading-edge research

Autonomy and continuous learning culture

Qualifications

• 3+ years of experience in a quantitative research or trading role.
• Deep understanding of systematic equity investing and statistical arbitrage frameworks.
• Strong mathematical and statistical skills.

Responsibilities

• Conduct research and development of systematic equities strategies.
• Analyze complex datasets to uncover trading signals.
• Collaborate with portfolio managers and data scientists.

Skills

Statistical arbitrage

Machine learning techniques

Python

Data analysis

Education

Advanced degree in Mathematics, Computer Science, Physics, Engineering, or Statistics

Tools

scikit-learn

TensorFlow

XGBoost

Job description

My client, a leading global hedge fund with a strong track record in systematic investing, is looking to hire a Quantitative Researcher to join their Singapore-based team. This is a unique opportunity to work on cutting-edge systematic equities strategies within a collaborative and research-driven environment.

The ideal candidate will bring a solid technical foundation and prior experience in the quantitative finance space, whether from another hedge fund, proprietary trading firm, or a front-office role in investment banking. A strong background in statistical arbitrage is essential, and exposure to machine learning techniques is a strong bonus.

Key Responsibilities

• Conduct research and development of alpha-generating systematic equities strategies, with a focus on statistical arbitrage.
• Analyze large, complex datasets to uncover new trading signals and improve existing models.
• Apply machine learning methods to improve predictive power and ensure robustness of strategies.
• Perform rigorous backtesting and optimization using a Python-based infrastructure.
• Collaborate closely with portfolio managers, data scientists, and technologists to deploy strategies into production.

Candidate Profile

• Prior experience (3+ years) in a quantitative research or trading role at a hedge fund, prop trading firm, or investment bank (front office).
• Advanced degree in a quantitative field such as Mathematics, Computer Science, Physics, Engineering, or Statistics.
• Deep understanding of systematic equity investing and statistical arbitrage frameworks.
• Proficient in Python for research and prototyping - experience with ML libraries (e.g., scikit-learn, TensorFlow, XGBoost) is a strong plus.
• Strong mathematical and statistical skills, with a keen eye for detail and performance optimization.
• Comfortable working independently and as part of a dynamic, fast-paced team.

What’s on Offer

• Opportunity to join a high-calibre team at a prestigious global hedge fund.
• Exposure to leading-edge research, infrastructure, and proprietary data.
• Competitive compensation package with strong performance incentives.
• A culture that values innovation, autonomy, and continuous learning.