Data Scientist, Quantitative Trading (NLU/NLP)

Binance; Singapore; On-site; SGD 90,000 - 120,000; Full time

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

NLP libraries: SpaCy, NLTK, HuggingFace Transformers

Named Entity Recognition (NER)

Sentiment Analysis

Intent Detection

Python programming

R for statistical modeling

Data manipulation: pandas, NumPy

Probability theory understanding

Linear algebra knowledge

Time-series analysis

Risk modeling

Statistical testing

Scikit-learn

TensorFlow

PyTorch

Text classification

Clustering

Financial markets knowledge

Quantitative trading concepts

Backtrader

Zipline

Fluency in English and Mandarin

Job description

Data Scientist, Quantitative Trading (NLU/NLP)

Crypto Jobs

Job Description

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

Required Technical Skills

• 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

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