Quantitative Trading Strategy Engineer

This is a fully remote position, open to applicants in Hong Kong, +2 more countries.

📋 Description

• Identify, develop, and validate trading factors utilizing market, fundamental, and on-chain data.

• Continuously enhance the factor library to uncover effective alpha signals.

• Design and refine machine learning and deep learning prediction models while managing overfitting and strategy decay.

• Lead the design of trading strategies, backtesting, and validation of live deployment.

• Oversee signal generation, portfolio construction, risk management, and execution optimization.

• Take ownership of strategy profit and loss (P&L) and risk performance.

• Construct and improve the comprehensive quantitative trading strategy pipeline from data ingestion and factor computation through model prediction, backtesting, and live execution.

• Enhance research efficiency, deployability, and reproducibility.

• Collaborate with engineering and data teams on data connectivity, low-latency execution, and strategy deployment.

• Ensure the stable operation of strategies in production.

• Investigate AI-driven trading across equities, futures, cryptocurrency, and on-chain asset markets.

⛳️ Requirements

• Master’s degree or higher in Computer Science, Mathematics, Statistics, Financial Engineering, Physics, or related fields, with a strong quantitative background and programming skills.

• Demonstrated experience in quantitative trading strategy research and development, familiar with the entire workflow of factor mining, factor prediction, strategy backtesting, and live deployment.

• Profound understanding of strategy P&L, risk, and alpha decay.

• Proficient in Python, with practical experience in applying ML/DL methods in quantitative contexts and handling large-scale financial time-series data.

• Knowledge of trading mechanisms and data characteristics in at least one market: equities, futures, traditional financial markets, cryptocurrency, or on-chain assets.

• Comprehension of trading costs, liquidity, and execution slippage.

• Experience in building a complete strategy pipeline or a quantitative research platform.

• Capability to independently deliver a full strategy loop from data to live trading.

• Strong research abilities and a results-oriented mindset.

• Proven track record of managing capital at scale in live trading or producing sustained alpha (bonus qualification).

• Cross-market quantitative experience covering traditional finance and on-chain markets (bonus qualification).

• Familiarity with high-frequency trading, market-making strategies, or cross-market arbitrage (bonus qualification).

• Practical experience in applying cutting-edge AI methods, including large language models and reinforcement learning, to trading strategies (bonus qualification).

🏝️ Benefits

• Competitive salary and company benefits

• Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)

• Opportunities for career growth and continuous learning

• Collaboration with world-class talent in a user-centric global organization with a flat structure

• Autonomy in an innovative environment

• Equal opportunity employer and diverse workforce