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Data Scientist, Quantitative Trading (NLU/NLP)
Job summary
A global crypto exchange is seeking a Data Scientist to leverage NLP and machine learning for quantitative trading. The role involves extracting trading signals from news and social media, building predictive models, and integrating insights into trading strategies. Candidates must have strong programming skills in Python, be proficient with various NLP techniques, and have a deep understanding of financial markets. Fluency in English and Mandarin is required.
Qualifications
- Proficient with NLP libraries including SpaCy and NLTK.
- Strong Python programming skills preferred.
- Experience with data manipulation libraries like pandas and NumPy.
Responsibilities
- Extract alpha from text-based sources such as Reddit and Twitter.
- Build ML/NLP models to predict market behavior.
- Integrate linguistic signals into backtested trading strategies.
Skills
Crypto Jobs
Title: Data Scientist – Quantitative Trading (NLU/NLP)
Department: Quantitative Trading / Research
Key Focus: Leverage NLP and machine learning to extract trading signals from news and social media
This role merges Natural Language Understanding (NLU) with quant finance. You’ll:
- Extract alpha from text-based sources (e.g., Reddit, Twitter, news feeds)
- Build ML/NLP models to predict market behavior
- Integrate linguistic signals into backtested trading strategies
- Proficient with NLP libraries: SpaCy, NLTK, HuggingFace Transformers
- Skilled in Named Entity Recognition (NER), Sentiment Analysis, and Intent Detection
- Experience extracting trading signals from unstructured text (news, social media)
- Strong programming skills in Python (preferred); familiarity with R for statistical modeling
- Experience with data manipulation using pandas, NumPy, and API integration
- Solid understanding of probability theory, linear algebra, and time-series analysis
- Knowledge of risk modeling and statistical testing for hypothesis validation
- Proficient in Scikit-learn, TensorFlow, and PyTorch for training, tuning, and deploying models
- Applied ML to text classification, clustering, and signal generation
- Familiarity with financial markets and quantitative trading concepts
- Experience using Backtrader, Zipline, or custom backtesting frameworks to simulate trading strategies
- Fluent in English and Mandarin to collaborate with global, cross-functional teams and stakeholders
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.
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