Quantitative Researcher / Developer

MS Capital Singapore; Hong Kong; Hybrid; HKD 800,000 - 1,200,000; Full time

Job summary

MS Capital’s technology arm seeks quantitative researchers to design systematic trading strategies and build robust data pipelines. The role involves extracting signals from diverse datasets, backtesting models, and maintaining data infrastructure for live trading across global markets.

You will collaborate with quants, PMs, and traders to translate research into production, leveraging Python/C++ and modern data tooling in a flexible, international environment.

Qualifications

• Degree in Computer Science, Mathematics, Engineering, Finance or a related field.
• Experience in quant research, data engineering, or systematic trading in hedge funds or asset managers.
• Strong programming skills in Python and/or C++.
• 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 data, microstructure, fundamentals, and alternatives.
• Design and implement robust backtesting and research pipelines.
• Build and maintain data infrastructure: ingestion, cleaning, normalization.
• Maintain security master and identifier mapping (ISIN, CUSIP, SEDOL, RIC, Bloomberg).
• Integrate data with OMS/EMS and prime broker systems for trading.
• Monitor data quality and model performance; resolve anomalies.
• Collaborate with PMs, quants, and traders to productionize research.

Skills

Quant research

Data engineering

Strong problem-solving

Learning agility

Education

Degree in Computer Science, Mathematics, Engineering, Finance or related field

Tools

Python

C++

Git

Job description

MS Capital is a private fund management company with a strong founding team with long-accumulated experience in strategy modelling, trading system and platform development. Using advanced artificial intelligence technology as the cornerstone, and enforcing strict investment management, the company's investment fund has gained sustained and stable returns.

You will be joining MS Capital's technology arm, with AL/ML as its cornerstone, and is committed to providing users with high-quality and stable trading services. The company now has a number of experienced quantitative researchers, world-class deep learning scientists and engineers from leading internet companies and top universities. The company has also provided various kinds of trading solutions for a number of leading brokerage firms and organizations. The company's vision is to integrate artificial intelligence technology with quantitative investment scenarios, relying on strong artificial intelligence R&D capabilities and advanced trading strategy models, to provide users with comprehensive and stable investment service.

Support for flexible working locations, including Hong Kong, Shenzhen, Shanghai, Singapore, etc.

• 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

Qualifications:

• Degree in Computer Science, Mathematics, Engineering, Finance or a related field.
• 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