Remote-Friendly Quantitative Researcher: AI-Driven Trading

MS Capital Singapore; Hong Kong; Hybrid; HKD 600,000 - 1,000,000; Full time

Job summary

MS Capital is seeking a talented Quant Researcher to join its technology arm in a role spanning research and data operations. You will develop systematic trading strategies, extract signals from diverse datasets, and build robust backtesting pipelines to support production trading initiatives.

You will work with a team of researchers and engineers, leveraging Python/C++ to deliver reliable data infrastructure and quantitative models for global markets.

Qualifications

• Experience in quant research, data engineering, or systematic trading in a hedge fund / asset manager / prop firm.
• Strong programming skills using Python / C++ or others.
• Familiarity with global equity markets and financial data.
• Strong problem-solving ability, attention to detail, and learning agility.

Responsibilities

• Research and develop systematic trading strategies across global markets.
• Extract signals from market, microstructure, fundamental, and alternative datasets to build quantitative models.
• Design and implement robust backtesting and research pipelines.
• Build and maintain data infrastructure, including data ingestion, cleaning, normalization, and standardization.
• Security master and identifier mapping (ISIN, CUSIP, SEDOL, RIC, Bloomberg).
• Integrate data with OMS/EMS and prime broker systems for trading and reconciliation.
• Monitor and improve data quality and model performance, resolving anomalies and ensuring reliability.
• Collaborate closely with PMs, quants, and traders to translate research into production.

Skills

Python

C++

Quant research

Data engineering

Education

Degree in Computer Science

Degree in Mathematics

Degree in Engineering

Degree in Finance

Job description

MS Capital is seeking a talented Quant Researcher to join its technology arm in a role spanning research and data operations. You will develop systematic trading strategies, extract signals from diverse datasets, and build robust backtesting pipelines to support production trading initiatives.

You will work with a team of researchers and engineers, leveraging Python/C++ to deliver reliable data infrastructure and quantitative models for global markets.