Binance is hiring a

Web3 Data Scientist, Quantitative Trading (NLU/NLP)

This role sits at the intersection of quantitative finance, machine learning, and natural-language understanding. You’ll leverage NLU techniques—like sentiment and intent analysis—to mine news and social media for trading signals, build and mathematically refine predictive models, and rigorously backtest and optimize your strategies to drive data-driven investment decisions.

Responsibilities:

• Research and develop quantitative trading strategies using NLU methods—sentiment analysis, intent recognition, named-entity extraction—on financial news, social media, and other text sources
• Design and build machine-learning models to uncover predictive trading signals and perform exploratory data analysis on large, complex datasets
• Apply mathematical techniques (probability, statistics, time-series analysis) to refine and strengthen trading models
• Rigorously backtest strategies against historical data and iteratively optimize models to boost performance and curb risk

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, Financial Engineering or a related discipline
• Solid grasp of NLU techniques, including sentiment analysis, intent recognition, and named-entity recognition
• Proficiency in Python or R, with hands-on experience in NLP libraries (SpaCy, NLTK, Transformers)
• Strong mathematical foundation—probability, statistics, linear algebra, time-series analysis—and familiarity with ML frameworks (Scikit-learn, TensorFlow, PyTorch)
• Excellent analytical and problem-solving abilities, with strong communication and teamwork skills
• Bilingual English/Mandarin is required to be able to coordinate with overseas partners and stakeholders.

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