Python Data Scientist (Quantitative Finance)

Python Data Scientist (Quantitative Finance) We are seeking a highly skilled and motivated Python Data Scientist to join our dynamic team with a minimum of 4 years of work experience. The ideal candidate will have extensive knowledge in quantitative finance, with a focus on FX or cryptocurrency trading. This position requires a strong foundation in Python programming and linear models, as well as proven experience in data mining. Key Responsibilities: - Collaborate with quantitative researchers to develop, tune, and refine trading models, ensuring optimal performance and accuracy. - Apply expertise in quantitative finance to analyse complex data sets and extract meaningful insights that can directly impact trading strategies. - Utilise Python to implement and maintain robust data analysis tools and algorithms. - Conduct extensive data mining to identify new trading opportunities and trends in the FX and cryptocurrency markets. - Develop and test linear and non-linear modelling techniques to improve predictive accuracy and model performance. - Prepare detailed analytics reports and communicate findings to stakeholders and team members to support data-driven decision-making. Requirements: - Proven experience as a Data Scientist with a strong background in Python programming. - Advanced knowledge in quantitative finance, particularly in FX or crypto trading. - Proficiency in linear models and their application in financial modelling. - Demonstrated experience in data mining and handling large, complex datasets. - Ability to work closely and effectively with quantitative researchers and other team members. - Strong analytical skills with a keen attention to detail. - Excellent communication and presentation skills. - This will be a remote position initially and then the candidate will be relocated to Dubai, UAE. Must be willing to relocate. Preferred Qualifications: - Advanced degree in Mathematics, Statistics, Computer Science, or a related field. - Experience with additional programming languages or analytical tools is a plus.