ML Quant Researcher: Crypto Derivatives & Market-Making

Unchain Data; Singapore; On-site; SGD 180,000 - 250,000; Full time

Job summary

Hytech is seeking a senior quantitative ML engineer to design, validate, and deploy machine learning models for crypto derivative market-making and systematic trading strategies. You will work with researchers, traders, and low-latency engineers to turn data-driven insights into production-ready systems.

Join a team applying time-series modelling and market microstructure research to optimize quoting performance, risk controls, and execution quality across multiple CEX venues.

Qualifications

• Advanced degree in a quantitative field (MS/PhD) required.
• 3+ years of hands-on ML modelling for systematic trading or related finance.
• Strong time-series ML and feature engineering for high-frequency data.
• Proficiency in Python and solid statistical foundations.
• Deep understanding of market microstructure and exchange APIs.
• Experience with backtesting frameworks and avoiding overfitting.
• Familiarity with streaming data and low-latency pipelines.
• Ability to communicate quantitative results to non-ML teams.

Responsibilities

• Design and validate ML models for market microstructure and alpha signals.
• Build backtesting, walk-forward validation, and robustness checks.
• Engineer features from high-frequency market data (order books, ticks, trades).
• Collaborate with traders and researchers to translate hypotheses into ML frameworks.
• Deploy models into low-latency trading systems with engineering teams.
• Develop dashboards to monitor model performance and drift.
• Document research findings and production constraints.

Skills

Time-series ML

Statistical modelling

Python programming

Communication of results

Education

Master's or PhD in quantitative field

Tools

Python (NumPy, Pandas)

PyTorch / TensorFlow

Kafka / PubSub / Redis streams

Docker

C++/Rust production systems

Job description

Hytech is seeking a senior quantitative ML engineer to design, validate, and deploy machine learning models for crypto derivative market-making and systematic trading strategies. You will work with researchers, traders, and low-latency engineers to turn data-driven insights into production-ready systems.

Join a team applying time-series modelling and market microstructure research to optimize quoting performance, risk controls, and execution quality across multiple CEX venues.