عالم بيانات

A Data Scientist is responsible for designing, building, and maintaining the infrastructure and systems required to process, store, and analyze large volumes of data efficiently. They enable data accessibility and usability for organizations by creating robust, scalable, and secure data pipelines and systems. The role involves collaboration with cross-functional teams, ensuring compliance with policies, and contributing to the continuous improvement of data processes. Also supports AI/ML initiatives by creating infrastructure for model training and deployment.

Job Responsibilities

Key Accountability Areas

Responsibilities

Data Scientist

• AI Transformation Programs: Lead AI transformation initiatives, executing multiple AI use cases such as fraud detection, collections optimization, customer service improvements, and next-best-action strategies.
• Financial Planning Platforms: Develop and manage financial planning platforms powered by GenAI, including hyper personalized long-term financial planning tools.
• Claims Transformation: Implement end-to-end claims transformation use cases, developing models and data pipelines for fraud detection and claims steering.
• Distribution Use Cases: Lead the development and deployment of models for cross-sell propensity, next-product-to-buy, and churn prediction.
• Pricing Use Cases: Develop technical price models, geospatial scoring models, vehicle classification models, elasticity models, and competitor price prediction models.
• Health Insurance Pricing: Design national health insurance pricing and risk management strategies, including actuarial modeling and financial projections.
• Data and Analytics Strategy: Develop data and analytics strategies, identify value-at-stake and support target operating models and roadmaps.
• Qualifications:
• Education: Qualified Actuary (FASSA)
• Experience: Minimum 4 years of experience in insurance and advanced analytics
• Skills: Expertise in AI, machine learning, data science, actuarial modeling, and business change management
• Leadership: Proven ability to lead teams of data scientists, data engineers, software engineers, and change management consultants

Requirements

Educational Background and Certifications:

Bachelor’s degree in any engineering degree, preferably with a background in mathematics or actuarial studies, or a related field.

Qualified Actuary (Fellow of the Actuarial Society)

Experience:

4+ years in insurance, actuarial science, and advanced analytics

Proven track record in leading AI and data science transformations