AI-Driven Quantitative Trading Strategy Intern

Binance; Hong Kong; Remote; HKD 134,000 - 201,000; Full time

Benefits offered by this job

Remote-first

Competitive salary and benefits

Job summary

Binance is seeking a Quantitative Trading Strategy Algorithm Intern to join its AI-driven trading initiative in Hong Kong. You will conduct research on factor discovery, prediction, and strategy construction across traditional and on-chain assets, applying Python and ML techniques to real-world data.

Responsibilities include factor validation, model design, backtesting, and building end-to-end R&D pipelines, with exposure to frontier AI-driven trading methods in a fast-paced environment.

Qualifications

• Current Master’s or PhD student in Computer Science, Mathematics, Statistics, Financial Engineering, Physics, or a related field, with a strong quantitative foundation and programming skills.
• Strong interest in quantitative trading strategies, familiarity with factor mining and strategy backtesting workflows.
• Proficient in Python, knowledgeable about ML/DL methods applied in quantitative scenarios, and experienced in handling financial time-series data.
• Understanding of trading mechanisms and data characteristics in at least one market (equities, futures, or other traditional financial markets; or crypto and on-chain assets).
• Strong learning ability and research enthusiasm, high initiative, and ability to continuously explore in a fast-iterating environment.

Responsibilities

• Participate in the discovery, construction, and validation of trading factors, exploring effective alpha signals from multi-source data including market data, fundamental data, and on-chain data.
• Participate in the design and optimization of factor prediction models, applying machine learning and deep learning methods to enhance signal predictive power and stability.
• Participate in the design, backtesting, and validation of trading strategies, assisting with signal generation, portfolio construction, and risk control research.
• Participate in building the quantitative trading strategy pipeline, helping to streamline the R&D workflow from data, factors, and models to backtesting.
• Track frontier methods in quantitative and AI-driven trading, conducting exploratory research that combines the market characteristics of traditional equities and on-chain assets.

Job description

Binance is seeking a Quantitative Trading Strategy Algorithm Intern to join its AI-driven trading initiative in Hong Kong. You will conduct research on factor discovery, prediction, and strategy construction across traditional and on-chain assets, applying Python and ML techniques to real-world data.

Responsibilities include factor validation, model design, backtesting, and building end-to-end R&D pipelines, with exposure to frontier AI-driven trading methods in a fast-paced environment.