Research Data Scientist, NLP & Financial Signals

Binance • Asia, GA

18h • Remote

About The Position

As a Data Scientist focusing on Quantitative Trading NLP, you will leverage natural language understanding techniques such as sentiment analysis, intent recognition, and named-entity extraction on financial news, social media, and other text streams to develop and refine algorithmic trading strategies. You’ll design and implement machine-learning models in Python, apply advanced mathematical and time-series analysis to uncover predictive signals, and rigorously backtest and optimize strategies to maximize returns while managing risk. Collaboration and clear communication across data science and trading teams are key to iteratively improving model performance and driving data-informed investment decisions.

Requirements

• At least 2 years of relevant experience in data science, machine learning, or natural language processing
• Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, Financial Engineering, or a related discipline
• Strong mathematical foundation: probability, statistics, linear algebra, time-series analysis, and familiarity with ML frameworks (Scikit-learn, TensorFlow, PyTorch)
• 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)
• A passion for exploring undefined problem spaces in the fast-changing crypto world

Responsibilities

• Research and develop quantitative trading strategies using NLU methods such as 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 optimise models to boost performance and curb risk

Benefits

• Shape the future with the world’s leading blockchain ecosystem
• Collaborate with world-class talent in a user-centric global organization with a flat structure
• Tackle unique, fast-paced projects with autonomy in an innovative environment
• Thrive in a results-driven workplace with opportunities for career growth and continuous learning
• Competitive salary and company benefits
• Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees