Quantitative Trading Strategy Algorithm Engineer

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world.

About the Role

We are building an AI-driven trading system that covers traditional financial assets (equities, etc.) and on-chain assets. We are seeking algorithmic researchers with deep understanding of trading strategies to participate in the full lifecycle — from factor mining and prediction to strategy construction and system integration — combining quantitative research expertise with AI technology to build a trading strategy system that generates sustainable alpha.

Responsibilities

• Factor Mining & Validation: Discover, construct, and validate trading factors from multi-source data including market data, fundamental data, and on-chain data. Continuously iterate the factor library to identify effective alpha signals.

• Factor Prediction Modeling: Design and optimize prediction models using machine learning and deep learning methods to improve signal accuracy and stability while controlling overfitting and strategy decay.

• Strategy Design & Backtesting: Lead the design, backtesting, and live deployment validation of trading strategies — covering signal generation, portfolio construction, risk control, and execution optimization. Take ownership of strategy P&L and risk performance.