Research Data Scientist NLP Financial Signals
## 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 • *The crypto industry is evolving rapidly, offering new opportunities in blockchain, web3, and remote crypto roles — don’t miss your chance to be part of it. Apply tot his job
Apply tot his job
Apply To this Job
Apply tot his job
Apply To this Job
Apply tot his job
Apply To this Job
Apply tot his job
Apply To this Job