Data Scientist, NLP & Trading Strategies (Quantitative)

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Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by over 280 million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world.

About the Role

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.

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.

Requirements

• 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 space in the fast changing crypto world.

Why Binance

• 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).

Binance is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success.

By submitting a job application, you confirm that you have read and agree to our Candidate Privacy Notice.

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How to Submit an Application:

After reading and knowing the criteria and minimum requirements for qualifications that have been explained from the Data Scientist, NLP & Trading Strategies (Quantitative) job info - Binance Hawke's Bay above, thus jobseekers who feel they have not met the requirements including education, age, etc. and really feel interested in the latest job vacancies Data Scientist, NLP & Trading Strategies (Quantitative) job info - Binance Hawke's Bay in 2025-10-28 above, should as soon as possible complete and compile a job application file such as a job application letter, CV or curriculum vitae, FC diploma and transcripts and other supplements as described above, in order to register and take part in the admission selection for new employees in the company referred to, sent via form this bottom.