Quantitative Trading Strategy Algorithm Engineer

New

BinanceCryptocurrency Blockchain

Hong Kong / Taiwan, Taipei / Australia, SydneyFull-TimeMiddle

Salary not disclosed

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Job Details

Master's degree or above in Computer Science, Mathematics, Statistics, Financial Engineering, Physics, or related fields.
Proven experience in quantitative trading strategy R&D, including the full workflow of factor mining, prediction, and backtesting.
Deep understanding of strategy P&L, risk management, and alpha decay.
Proficiency in Python with hands-on experience in machine learning and deep learning for quantitative finance.
Experience processing large-scale financial time-series data.
Familiarity with trading mechanisms and data characteristics of traditional financial markets or cryptocurrency/on-chain assets.
Understanding of real-world trading factors such as costs, liquidity, and execution slippage.
Experience building a complete quantitative strategy pipeline or research platform.
Ability to independently deliver end-to-end strategy loops from data to live trading.
Strong research capability and results-driven mindset for fast-iteration environments.

Discover, construct, and validate trading factors from multi-source market, fundamental, and on-chain data.
Design and optimize prediction models using machine learning and deep learning to enhance signal accuracy.
Lead the full strategy lifecycle, including backtesting, risk control, execution optimization, and live deployment validation.
Develop and refine end-to-end quantitative trading pipelines from data ingestion to live strategy execution.
Collaborate with engineering teams to ensure data connectivity, low-latency execution, and production stability.
Explore AI-driven trading strategies across both traditional financial and on-chain asset markets.

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