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:

• 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, 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 spaces in the fast-changing crypto world

• Shape the future with the world’s leading blockchain ecosystem
• Collaborate with world-class talent in a user-centric global organization with a flat structure
• Tackle unique, fast-paced projects with autonomy in an innovative environment
• Thrive in a results-driven workplace with opportunities for career growth and continuous learning
• Competitive salary and company benefits
• Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.