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Role Overview

As a Data Scientist, you will build and deploy machine learning and computer vision models that power our motor insurance products, from automated damage assessment to claims triage and risk pricing. Based at our Eastern Region office, you'll work closely with cross-functional teams in a HYBRID environment to turn data into production-grade capabilities, improve decision accuracy, and drive analytical excellence within our organization.

Responsibilities

• Develop, train, and deploy computer vision models for motor use cases such as vehicle damage detection, severity estimation, part identification, and image fraud checks.
• Build predictive models supporting claims triage, loss ratio forecasting, reserving, pricing, and fraud detection.
• Design and maintain data pipelines for image, telematics, policy, and claims datasets, including labelling workflows and dataset quality controls.
• Partner with claims, underwriting, and product teams to frame business problems as measurable data science problems.
• Evaluate model performance in production, monitor for drift, and run experiments and A/B tests to validate impact.
• Work with engineering to productionize models through APIs, containerized services, and cloud ML tooling.
• Translate model outputs into clear insights and recommendations for business and management stakeholders.
• Prepare detailed reports, dashboards, and analytics for management review.
• Document methodology, assumptions, and model governance artefacts in line with regulatory and internal standards.
  
  

• Proven experience as a Data Scientist delivering models into production, not only research or proof-of-concept work.
• Hands-on computer vision experience, including deep learning frameworks such as PyTorch or TensorFlow and practical work with image datasets, detection, segmentation, or classification.
• Experience in the insurance sector, with a solid understanding of claims, underwriting, or pricing data.
• Demonstrated motor or automotive related project experience, for example vehicle damage assessment, telematics, driver behaviour, repair cost estimation, or accident analysis.
• Strong Python skills and proficiency with the standard data stack, including pandas, NumPy, scikit-learn, and SQL.
• Strong analytical, problem-solving, and statistical reasoning skills.
• Outstanding communication abilities, including the ability to explain technical work to non-technical stakeholders.
  
  

• Experience with cloud ML platforms on GCP or Azure, including Vertex AI or Azure ML.
• Familiarity with MLOps practices, model monitoring, versioning, and CI/CD for models.
• Experience with vision-language models, OCR, or document intelligence for claims processing.
• Exposure to model governance, explainability, and regulatory expectations for AI in insurance.
• Background in geospatial data, telematics, or IoT sensor data.
• Arabic and English fluency.
  
  

• Employee Stock Ownership Plan (ESOP).
• Flexible hybrid work arrangements.
• Opportunities for career growth and professional development.
• Collaborative, innovative work culture.