AI & Data Transformations Lead

Reporting to the Group Head of Technology, the AI & Data Transformation Lead is the strategic and technical guide of the section, combining deep domain knowledge of reinsurance with expertise in programming, AI usage, business analysis methodologies, and enterprise process transformation and automation. The role enables claims analytics, fraud detection, regulatory reporting, actuarial analysis, and operational dashboards, while ensuring data quality and compliance.

• Lead business analysis across all 18+ departments to map current-state processes, identify pain points, design future-state automated workflows and drive their implementation.
• Develop and maintain the organization's AI roadmap, including use-case identification, feasibility analysis, and phased deployment.
• Engage with external partners, brokers, and technology vendors to benchmark transformation initiatives against global best practice.
• Mentor the Transformation Officer and coordinate ICT resource requests servers, databases, APIs, cloud compute.
• Implement data quality checks, validation rules, and anomaly detection.
• Enforce secure data access using IAM, encryption, and role-based controls.
• Ensure compliance with Kenya Data Protection Act 2019 and healthcare confidentiality standards.
• Assess AI-related risks model bias, data drift, explainability, regulatory non-compliance and recommend mitigation controls.
• Review and recommend updates to Standard Operating Procedures SOPs to accommodate AI-driven decision support and automated processes.
• Chair the monthly Data Lock and Backup process, ensuring immutable snapshots are captured at midnight on the last day of each month.
• Design and implement real-time and batch data pipelines from insurance core systems and microservices.
• Build and operate event-driven data flows using Kafka Confluent and Amazon SQS.
• Support near-real-time processing for claims, authorizations, payments, and member events.
• Design and maintain insurance and healthcare data models members, policies, benefits, claims, providers, payments.
• Oversee the design of standard data tables, master data dictionaries, and unified access frameworks for cross-departmental analytics.
• Manage database schema changes using Liquibase.
• Ensure data consistency, reconciliation, and controlled schema evolution.
• Build and manage AWS-based data platforms, including data lakes and analytics layers.
• Support downstream use cases including BI reporting, actuarial modelling, and AI/ML initiatives.
• Optimize data pipelines for performance, scalability, and cost.
• Monitor data pipelines using Datadog.
• Document data flows, schemas, and integration points.
• Collaborate with API teams using OpenAPI standards where data services are exposed.
• Design and drive implementation of Group data-lake-based continuity solutions for East Africa, covering all core business data members, policies, pricing, benefits, claims, providers, payments.
• Work with internal and external specialists to develop AI agents that support data validation, anomaly/fraud detection and automation of operational workflows, and accelerate migration or re-platforming by reconstructing

• Bachelor of Science in Information Technology, Computer Science or a related field, or equivalent experience
• Confluent Certified Developer for Apache Kafka
• Databricks Data Engineer
• Master's degree in Data Science/Analytics
• AWS Certified Data Analytics Specialty
• AWS Certified Solutions Architect Associate
• Google Professional Data Engineer