Senior Data Scientist

Location: Abu Dhabi, UAE (relocation support provided)

Compensation: £120,000–£300,000 total compensation (fully guaranteed, all-in)

We are building a centralised data function supporting quantitative research and development teams. The role focuses on large-scale unstructured and alternative data and applies statistical and machine learning methods. Much of the work is greenfield, with responsibility for defining data, modelling, and experimentation standards from first principles.

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• Build and own ML models and data workflows on large, messy datasets
  
• Design experiments to assess data structure, signal quality, and robustness
  
• Develop forecasting, modelling, or optimisation systems that inform decisions
  
• Analyse model behaviour, regime shifts, drift, and failure modesTranslate modelling work into production-grade components
  
• Own models end-to-end, including monitoring and iteration
  

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• Strong foundations in statistics, probability, and applied machine learning
  
• Fluent Python with experience writing production-quality, testable code
  
• Hands-on experience with large, noisy datasets
  
• Demonstrated impact through shipped models, production systems, or original work
  

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• Market, macroeconomic, or financial time-series data
  
• Commodities, energy, or asset-level datasets
  
• Equities-related data (earnings, filings, corporate disclosures)
  
• Alternative or unstructured data used in modelling or forecasting (e.g. transactions, text, imagery, sensor data)
  
• Forecasting, scenario analysis, optimisation, or risk-aware modelling
  

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• Fully guaranteed, competitive compensation
  
• Education allowance for dependent children
  
• 30 working days of annual leave
  
• Comprehensive healthcare for employee and family
  
• Business class relocation flights
  
• Joining and departure allowances
  

The role is on-site in Abu Dhabi. Short-term remote work during the peak summer months is supported, along with generous leave and public holidays. The working model is designed for long-term sustainability and family life.

Send your CV and a brief summary of relevant experience to