Data Scientist (AI & Advanced Analytics)

Role overview

Responsibilities

• Develop, deploy, and maintain AI and machine-learning models for business use cases.
• Analyze structured and unstructured data and provide actionable business insights and recommendations.
• Collaborate with business and technology stakeholders to identify challenges and deliver data-driven solutions.
• Develop and maintain data pipelines, feature-engineering processes, and model-monitoring frameworks.
• Build predictive analytics for customer, risk, and operational insights.
• Implement Generative AI, LLM, NLP, and advanced analytics initiatives.
• Monitor model performance, scalability, accuracy, and reliability, and improve models as needed.
• Ensure solutions meet AI governance, risk-management, regulatory, and compliance requirements.
• Present findings and recommendations to business stakeholders and executive leadership.
• Collaborate across teams to deliver scalable, production-ready AI solutions.

Experience and technical requirements

• 7–10 years of experience in data science, artificial intelligence, machine learning, or a related field.
• Strong expertise in Python, SQL, machine learning, deep learning, and statistical modeling.
• Hands-on experience with LLMs, Generative AI, and NLP, plus at least one of TensorFlow, PyTorch, or Scikit-learn.
• Strong experience in predictive analytics and advanced data solutions.
• Experience developing and deploying scalable AI/ML models and data pipelines.

Industry and communication requirements

• Banking or financial-services experience is mandatory.
• Strong understanding of AI governance, model risk management, regulatory requirements, and compliance standards.
• Strong analytical, problem-solving, communication, and stakeholder-management skills; able to explain complex findings as business recommendations.
• Arabic speaking is required.
• Experience working with senior management and executive stakeholders is preferred.