Quantitative Developer

MS Capital Singapore; Singapore; On-site; SGD 70,000 - 110,000; Full time

Job summary

MS Capital, Singapore-based private fund management company, seeks a data/quant tech specialist for its technology arm focusing on AI/ML-driven trading data. You will ingest and standardize global equity data, maintain tickers and identifiers, and collaborate with PMs and quants to support reliable research and trading.

The role emphasizes strong Python/SQL skills and familiarity with major data vendors. Qualification in CS/engineering and finance experience is valued.

Qualifications

• Degree in computer science, engineering or related field.
• Experience with global equity markets (US, Europe, APAC).
• Strong Python (Pandas, NumPy) and SQL skills.
• Familiarity with financial data vendors and equity reference/pricing data.
• Understanding of security identifiers (ISIN, CUSIP, SEDOL, RIC, Bloomberg ticker).
• Experience in hedge funds, prop trading firms, or asset managers preferred.
• Exposure to tick or intraday data and buy-side OMS/EMS systems is a plus.

Responsibilities

• Ingest, clean, and maintain global equity market data from vendors (Bloomberg, Refinitiv, FactSet, exchanges).
• Standardize datasets for quantitative research, factor models, and portfolio construction.
• Track and process corporate actions (ticker changes, mergers, spin-offs, delistings).
• Maintain symbol and identifier mappings across exchanges and systems.
• Collaborate with PMs, quants, and trading teams to deliver reliable data for research and trading.
• Map prime broker and OMS/EMS tickers for execution and post-trade reconciliation.
• Monitor data quality and resolve data breaks, errors, and anomalies.

Skills

Python (Pandas, NumPy)

SQL

Financial data analysis

Equity markets knowledge

Security identifiers (ISIN/CUSIP/SEDOL

Education

Degree in Computer Science or Engineering or related field

Tools

Bloomberg

Refinitiv

FactSet

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.

• Ingest, clean, and maintain global equity market data from vendors such as Bloomberg, Refinitiv, FactSet, and exchanges.
• Standardize datasets for use in quantitative research, factor models, and portfolio construction.
• Track and process corporate actions (ticker changes, mergers, spin-offs, delistings, ADR vs. local shares).
• Maintain symbol and identifier mappings across exchanges, time zones, and trading systems.
• Work closely with PMs, quants, and trading teams to deliver reliable research and trading data.
• Map prime broker and OMS/EMS tickers for execution and post-trade reconciliation.
• Monitor data quality and resolve breaks, errors, and anomalies.

Qualifications:

• Degree in Computer Science, Engineering, or a related field.
• Experience with global equity markets (US, Europe, APAC).
• Strong Python (Pandas, NumPy) and SQL skills.
• Familiarity with financial data vendors and equity reference/pricing data.
• Understanding of security identifiers (ISIN, CUSIP, SEDOL, RIC, Bloomberg ticker).
• Experience in a hedge fund, prop trading firm, or asset manager is preferred.
• Exposure to tick or intraday data and buy-side OMS/EMS systems is a plus.