Research Data Scientist, NLP, Financial Signals
Binance
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇹🇼 Taiwan
Visit company websiteJob Level
Mid-LevelSenior
Tech Stack
PythonPyTorchScikit-LearnTensorflow
About the role
- 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
Benefits
- Competitive salary and company benefits
- Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
quantitative trading strategiessentiment analysisintent recognitionnamed-entity extractionmachine-learning modelsexploratory data analysisprobabilitystatisticstime-series analysisNLU techniques
Soft skills
problem-solvinganalytical thinkingadaptability