Data Scientist, NLP & Trading Strategies (Quantitative)

About the company

Binance operates a major global blockchain ecosystem and runs the world’s largest cryptocurrency exchange by trading volume and registered users. More than 300 million people across over 100 countries rely on its platform for security, fund transparency, fast matching engines, strong liquidity, and a broad suite of digital-asset products. Its services span trading, finance, education, research, payments, institutional solutions, Web3 capabilities, and related offerings, all aimed at expanding financial access and supporting the wider freedom of money.

Role overview

This position is for a Data Scientist working at the intersection of quantitative trading and natural language processing. The focus is on extracting signals from financial news, social media, and other text-based sources using techniques such as sentiment analysis, intent detection, and named-entity extraction, then turning those signals into trading strategies.

You will create machine-learning models in Python, use advanced statistical and time-series methods to identify predictive patterns, and validate strategies through rigorous backtesting. The role also requires close teamwork and strong communication with data science and trading teams to continuously improve model quality and support better investment decisions.

Responsibilities

• Build and research quantitative trading approaches using NLU methods across financial news, social platforms, and other text feeds, including sentiment analysis, intent recognition, and named-entity extraction.
• Develop machine-learning models that help surface predictive trading signals and perform exploratory analysis on large, complex datasets.
• Use probability, statistics, linear algebra, and time-series techniques to strengthen and fine-tune trading models.
• Backtest strategies thoroughly on historical data and keep improving them to increase performance while controlling risk.

Requirements

• Minimum 2 years of experience in data science, machine learning, or NLP-related work.
• Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, Financial Engineering, or a similar field.
• Strong command of core mathematics, including probability, statistics, linear algebra, and time-series analysis, along with familiarity with ML frameworks such as Scikit-learn, TensorFlow, or PyTorch.
• Good understanding of NLU approaches such as sentiment analysis, intent recognition, and named-entity recognition.
• Proficiency in Python or R, plus practical experience with NLP toolkits like SpaCy, NLTK, and Transformers.
• Interest in tackling open-ended problems in the rapidly evolving crypto environment.

Additional information

Binance positions itself as an equal opportunity employer and states that a diverse workforce is essential to its success.

Applicants confirm that they have reviewed and accepted the Candidate Privacy Notice when submitting an application.

The company notes that AI tools may support parts of the recruitment process, such as application review, resume analysis, response assessment, and inconsistency detection, but human judgment remains central and final hiring decisions are made by people.

Why join Binance

• Contribute to a leading blockchain ecosystem shaping the future of digital finance.
• Work with top-tier talent in a global, user-focused organization that operates with a flat structure.
• Take ownership of fast-moving, high-impact work in a highly innovative setting.
• Enjoy a performance-oriented environment with room for growth and ongoing learning.
• Receive a competitive compensation package and company benefits.
• Work-from-home flexibility may be available depending on the team’s business needs.