Quantitative Researcher

HashKey Liquid Funds; Singapore; On-site; SGD 120,000 - 210,000; Full time

Job summary

HashKey Capital in Singapore is seeking a Quantitative Researcher to join a small, end-to-end team responsible for idea generation, data work, implementation and live deployment of trading strategies. You will design and backtest market-making and systematic strategies, analyze market microstructure, and build models using order-book, trade, funding and on-chain data with Python and Rust.

Collaboration with traders and engineers is essential.

Qualifications

• Degree in mathematics, physics, statistics, computer science or engineering.
• 0–5 years in quantitative research, systematic trading or market making in crypto or traditional markets.
• Solid understanding of markets: order-book dynamics, adverse selection, inventory and funding risk.
• Strong Python for research and data analysis; Rust preferred; C++/Java useful.
• Comfortable with large, noisy, irregularly sampled datasets and stats to draw careful conclusions.
• Disciplined about risk, monitoring and documentation when several strategies run simultaneously.
• Curious, self-directed and precise; able to communicate with researchers and engineers.

Responsibilities

• Research, design, and implement market-making and systematic trading strategies from prototype to live trading.
• Analyze market microstructure across venues and adapt strategies accordingly.
• Build predictive models from order-book, trade, funding, and on-chain data using statistical and machine-learning methods; backtest and simulate.
• Monitor and improve live strategies: review parameters, diagnose P&L and inventory behavior, iterate with traders/engineers.
• Contribute to research infrastructure – simulation, backtesting and data pipelines – in Python and Rust.
• Evaluate new venues, instruments, protocols and data sources for new strategies.

Skills

Quantitative reasoning

Backtesting

Data analysis

Market understanding

Education

Quantitative discipline degree

Tools

Python

Rust

C++

Java

Job description

Quantitative Researcher

Singapore HashKey Capital

About The Position

We are looking for a Quantitative Researcher to join a small team that owns strategies end-to-end: from idea and data, through implementation and deployment, to live performance. The set of markets and strategies we run is growing quickly, and you will be trusted with real responsibility early.

What You'll Do

• Research, design, and implement market-making and systematic trading strategies, and take them from prototype to live trading.
• Analyze market microstructure across venues with very different fee, latency, funding, and settlement mechanics, and adapt strategies accordingly.
• Build predictive models from order-book, trade, funding, and on-chain data using statistical and machine-learning methods, and validate them with rigorous backtesting and simulation.
• Monitor and improve live strategies: review parameters, diagnose P&L and inventory behavior, and iterate quickly with traders and engineers.
• Contribute to research infrastructure - simulation, backtesting and data pipelines - in Python and Rust.
• Evaluate new venues, instruments, protocols and data sources as candidates for new strategies.

About You

• Degree in a quantitative or technical discipline (e.g. mathematics, physics, statistics, computer science, engineering); advanced degree welcome but not required.
• 0-5 years of experience in quantitative research, systematic trading or market making, in crypto or traditional markets. We strongly prefer candidates who have taken at least one strategy through the full cycle - research, implementation, live trading and post-trade review - and will also consider exceptional new graduates.
• A real understanding of how markets work - order-book dynamics, adverse selection, inventory and funding risk - and the judgment to tell a sound idea from a backtest artifact.
• Strong Python for research and data analysis. Rust is strongly preferred; experience with C++ or Java is useful.
• Comfortable with large, noisy, irregularly sampled datasets and with the statistics needed to draw careful conclusions from them.
• Disciplined about risk, monitoring and documentation when several strategies are running at once.
• Curious, self-directed and precise; comfortable with ambiguity and rapid iteration, and communicates clearly with both researchers and engineers.

Nice to Have

• Hands-on experience in liquidity provision or execution, in CeFi or DeFi (e.g. centralized perpetual venues, AMMs, on-chain order books).
• Exposure to derivatives beyond linear perpetuals, or to funding-rate and basis strategies.
• Familiarity with tokenized real-world assets, or with traditional exchange microstructure that transfers to them.
• Production Rust experience, or experience porting research code into a low-latency trading system.
• Working knowledge of exchange APIs, real-time market-data systems and on-chain data.
• Track record in competitive quantitative challenges (e.g. Kaggle, ICPC, trading competitions, mathematical olympiads).