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MS Capital Singapore Tech Stack

AI-powered hedge fund with proprietary trading algorithms

Financial Services Singapore, Singapore 11–50 employees Founded 2022 Privately Held

MS Capital is a quantitative hedge fund built on Python, C++, and financial data APIs (Bloomberg, Refinitiv, FactSet), currently scaling two core automation projects: agent-based trading and signal generation from ingested data. The hiring mix—three engineering roles, one data role, and one executive slot—reflects a fund still in early growth mode, with engineering-to-business ratios typical of firms moving from research prototypes toward production trading systems. Pain points around dataset standardization and corporate-action tracking suggest the team is building out real-time data infrastructure as trading volume increases.

Tech Stack 10 technologies

Core StackPython Pandas NumPy C++ RAG SQL Bloomberg Refinitiv FactSet

What MS Capital Singapore Is Building

◆Challenges

Standardizing datasets
Tracking corporate actions
Automating trading and research
Improving office efficiency and compliance

▲Active Projects

Agent-based trading automation
Data ingestion to signal generation automation

Hiring Activity

Steady7 roles · 2 in 30d

Department

Engineering

3

Data

1

Executive

1

Support

1

Seniority

Mid

3

Intern

2

Senior

1

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About MS Capital Singapore

MS Capital is a technology-driven hedge fund founded in 2022 and based in Singapore. The firm operates a proprietary quantitative trading platform powered by machine learning and algorithmic models. Operations center on two parallel workstreams: automating agent-based trading logic and building data pipelines that convert raw market feeds (via Bloomberg, Refinitiv, FactSet) into tradeable signals. The team is currently 11–50 people, hiring steadily across engineering and data roles in Singapore.

HeadquartersSingapore, Singapore

Company Size11–50 employees

Founded2022

Hiring MarketsSingapore

Frequently Asked Questions

What tech stack does MS Capital use?

Python, Pandas, NumPy, SQL, C++, and financial data terminals (Bloomberg, Refinitiv, FactSet). They also employ RAG (retrieval-augmented generation) for research automation.

What is MS Capital working on?

Two main projects: agent-based trading automation and data ingestion to signal generation automation. Both aim to reduce manual research and execution overhead.