Quantitative Trading Strategy Algorithm Engineer
Overview
Binance operates as a top global blockchain ecosystem, hosting the largest cryptocurrency exchange by trading volume and user base globally. Trusted by over 300 million individuals across 100+ nations, Binance prioritizes security, transparency in user funds, high-speed trading engines, liquidity, and a diverse range of digital asset products. Our offerings span trading, finance solutions, education, research, payments, institutional services, Web3 functionalities, and more. Through the impactful utilization of blockchain and digital assets, we endeavor to construct a financially inclusive ecosystem that advances financial access and the freedom of money universally.
Role
We are in the process of developing an AI-powered trading platform covering both conventional financial assets (e.g., equities) and on-chain assets. We are in search of skilled algorithmic researchers well-versed in trading strategies to contribute across the entire lifecycle of the system. This entails everything from mining and predicting factors to constructing strategies and integrating them into a system, combining expertise in quantitative research with AI technology to establish a trading strategy system that generates enduring alpha returns.
Responsibilities
Factor Discovery & Validation: Identify, formulate, and validate trading factors from diverse data sources encompassing market, fundamental, and on-chain data. Continuously enhance the factor library to pinpoint effective alpha signals.
Factor Prediction Modeling: Develop and optimize prediction models utilizing machine learning and deep learning techniques to enhance signal precision and stability while managing overfitting.
Strategy Development & Testing: Spearhead the design, backtesting, and live deployment validation of trading strategies focusing on signal generation, constructing portfolios, risk management, and optimizing executions.
Quant Strategy Pipeline Setup: Establish and refine the entirety of the quantitative trading strategy pipeline, spanning data aggregation, factor computation, model predictions, backtesting, and live executions to enhance research efficiency and implementability.
System Integration for Trading: Collaborate with engineering and data teams to resolve technical obstacles pertaining to data connectivity, low-latency executions, and strategy deployment to ensure reliable strategy operation within production environments.
AI Trading Across Markets: Investigate and implement AI-powered trading across traditional financial markets as well as on-chain asset markets, leveraging the unique characteristics of each market.
Requirements
Educational Qualifications: Hold a Master's degree or higher in Computer Science, Mathematics, Statistics, Financial Engineering, Physics, or related disciplines exhibiting a robust quantitative background and programming skills.
Experience: Proven background in quantitative trading strategy research and development encompassing factor discovery, prediction, backtesting, and live deployment. Profound comprehension of strategy performance metrics, risk evaluation, and alpha decay.
Technical Skills: Proficiency in Python with hands-on experience in applying ML/DL techniques to quantitative scenarios and working with substantial financial time-series data.
Market Knowledge: Proficient in the trading mechanisms and data peculiarities of at least one market, be it equities, futures, traditional finance, cryptocurrencies, or on-chain assets. Understanding real-world factors such as trading costs, liquidity, and execution slippage.
Pipeline Development Proficiency: Prior experience constructing a complete strategy pipeline or a quantitative research platform and independently delivering end-to-end strategy cycles from data capture to live trading.
Research Abilities: Demonstrated capability in robust research methodologies and a results-oriented mindset for ongoing optimization of strategy performance within a dynamic working environment.
Bonus Qualifications
Track Record: Demonstrable experience overseeing considerable capital in live trading or consistently generating alpha returns.
Cross-Market Expertise: Experience spanning both traditional finance and on-chain markets like DeFi, CEX, DEX.
Specialized Knowledge: Familiarity with high-frequency trading, market-making strategies, or cross-market arbitrage.
Cutting-Edge AI Usage: Practical application of advanced AI methods such as large language models or reinforcement learning to trading strategies.
Why Binance
Contribute to shaping the future within a premier blockchain ecosystem.
Collaborate with exceptional talent in a user-centric global organization offering a flat structure.
Engage in distinct, fast-paced projects with independence in an innovative setting.
Flourish in a results-driven environment with paths for career progression and continuous learning.
Competitive compensation and comprehensive company benefits.
Remote work flexibility based on the nature of team operations.
