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Binance | Brisbane, Australia |
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Data Scientist, NLP & Trading Strategies (Quantitative)
Asia / Australia, Brisbane / Australia, Melbourne / Australia, Sydney / Hong Kong / New Zealand, Auckland / New Zealand, Wellington / Taiwan, Taipei
Engineering – Data Science/AI /
Full-time: Remote /
Remote
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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.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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What is a quantitative career?
A quantitative career is a profession that involves using mathematical, statistical, and computational techniques to solve problems and make decisions in a wide range of industries, including finance, engineering, healthcare, and technology
A quantitative career in Web3 involves using mathematical, statistical, and computational techniques to analyze and optimize decentralized finance (DeFi) protocols, blockchain networks, and other Web3 applications
Some examples of quantitative careers include:
- Quantitative Analyst: A professional who uses mathematical models and statistical analysis to identify and quantify risks and opportunities in financial markets.
- Data Scientist: A professional who analyzes complex data using statistical methods, machine learning, and other techniques to help organizations make data-driven decisions.
- Actuary: A professional who uses mathematical models and statistical analysis to assess risk and uncertainty in the insurance and finance industries.
- Quantitative Developer: A professional who develops and implements quantitative models and trading strategies for financial institutions and other organizations.
- Operations Research Analyst: A professional who uses mathematical and statistical techniques to optimize complex systems, such as supply chains, transportation networks, and manufacturing processes.