Data Scientist, NLP & Trading Strategies
New
Australia, Brisbane; Australia, Melbourne; Australia, Sydney; Hong Kong; New Zealand, Auckland; New Zealand, Wellington; Taiwan, Taipei; AsiaFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- At least 2 years
- Required Skills
- PythonMachine LearningNLTKRNLP
Requirements
- At least 2 years of relevant experience in data science, machine learning, or natural language processing
- 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
- 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
- Hands-on experience in NLP libraries (SpaCy, NLTK, Transformers)
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
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