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Python Data Scientist (Quantitative Finance)

OTS Capital London, Vereinigtes Königreich
Gepostet vor 1 Tag Home Office Festanstellung 0
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.

 

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