Quantitative Trading Strategy Engineer

🔥 3 minutes ago

🌐 Hong Kong, Taiwan, +1 more countries – Remote

🇭🇰 Hong Kong – Remote 🇹🇼 Taiwan – Remote 🇦🇺 Australia – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

👷🏻‍♀️ Engineer

👻 Ghost score 11%

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Binance

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2017

₿ Crypto

💳 Fintech

💰 Initial Coin Offering on 2020-12

Crypto • Fintech

Binance is the world's leading cryptocurrency exchange, serving over 235 million registered users across more than 180 countries. The platform offers a wide array of services, including the trading of over 350 cryptocurrencies in Spot, Margin, and Futures markets. Users can also buy and sell crypto via Binance P2P, earn interest through Binance Earn, and engage in NFT trading on the Binance NFT marketplace. Binance provides low transaction fees and diverse payment options, making it a preferred choice for cryptocurrency enthusiasts worldwide.

📋 Description

• Discover, construct, and validate trading factors from market, fundamental, and on-chain data. • Continuously iterate the factor library to identify effective alpha signals. • Design and optimize machine learning and deep learning prediction models while controlling overfitting and strategy decay. • Lead trading strategy design, backtesting, and live deployment validation. • Cover signal generation, portfolio construction, risk control, and execution optimization. • Own strategy P&L and risk performance. • Build and refine the end-to-end quantitative trading strategy pipeline from data ingestion and factor computation through model prediction, backtesting, and live execution. • Improve research efficiency, deployability, and reproducibility. • Collaborate with engineering and data teams on data connectivity, low-latency execution, and strategy deployment. • Ensure stable strategy operation in production. • Explore AI-driven trading across equities, futures, cryptocurrency, and on-chain asset markets.

🎯 Requirements

• Master's degree or above in Computer Science, Mathematics, Statistics, Financial Engineering, Physics, or related fields, with a solid quantitative foundation and programming proficiency. • Proven experience in quantitative trading strategy R&D, familiar with the full workflow of factor mining, factor prediction, strategy backtesting, and live deployment. • Deep understanding of strategy P&L, risk, and alpha decay. • Proficient in Python, with hands-on experience applying ML/DL methods in quantitative scenarios and processing large-scale financial time-series data. • Familiarity with trading mechanisms and data characteristics of at least one market: equities, futures, other traditional financial markets, cryptocurrency, or on-chain assets. • Understanding of trading costs, liquidity, and execution slippage. • Experience building a complete strategy pipeline or quantitative research platform. • Ability to independently deliver an end-to-end strategy loop from data to live trading. • Strong research capability and results-driven mindset. • Track record of managing capital at scale in live trading or generating sustained alpha (bonus qualification). • Cross-market quantitative experience spanning traditional finance and on-chain markets (bonus qualification). • Familiarity with high-frequency trading, market-making strategies, or cross-market arbitrage (bonus qualification). • Practical experience applying frontier 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