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Binance
Binance

Data Scientist, Quantitative Trading (NLU/NLP)

Location

Remote anywhere

Salary Estimate

N/AIconOpenNewWindows

Seniority

N/A

Tech stacks

Blockchain
Data
Analysis
+27

Permanent role
7 days ago
Apply now

Data Scientist, Quantitative Trading (NLU/NLP)

Asia / Taiwan, Taipei / Thailand, Bangkok / Australia, Brisbane / Australia, Melbourne / Australia, Sydney

Engineering – Data Science/AI /

Full-time: Remote /

Remote

Apply for this job

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 250 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

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.

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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About Binance

👥201-500
📍Valletta, NA - Malta, Malta
🔗Website

Binance Service

Binance product / service
Binance product / service
Binance product / service
Binance product / service
Binance product / service

How does Binance work?

the world’s leading blockchain and cryptocurrency infrastructure provider with a financial product suite that includes the largest digital asset exchange by volume

Company culture

User-Focused

We protect our users by putting our users' needs first and delivering quality service.

Hardcore

We are results driven. We get things done. We are passionate and work hard. When we fail, we learn fast, and pick ourselves up.

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