Key Responsibilities
- Support the Data Intelligence and Reporting Manager with setting the data provisioning and democratization strategical direction and roadmap.
Ensure that data intelligence and reporting projects align with organizational goals
- Data Management & Analysis: Conduct exploratory and advanced statistical analysis to identify trends, patterns, and anomalies in insurance data. Ensure data integrity, accuracy, and governance standards are met.
- Reporting & Visualization: Develop interactive dashboard, workflows and reports (Power BI and Alteryx), providing actionable insights to business units (underwriting, claims, operations, actuarial, sales, customer service).
- Business Insights: Perform root cause analysis on claims leakage, fraud patterns, and operational bottlenecks.
- Collaboration & Stakeholder Management: Partner with business teams (Operations, IT, Risk, Compliance, Finance) to define data requirements and KPIs.
- Contribute to data democratization by enabling self-service reporting for business teams.
- Data Products Development: Design, build, and maintain data products such as; Customer 360 datasets / profiling, Claims performance dashboards for operational monitoring and leakage detection, Fraud detection models embedded as reusable analytics components, Pre-approval turnaround trackers for real-time SLA monitoring and Enable self-service data products for business teams, allowing them to access governed and trusted datasets without IT dependency.
Key Skills & Competencies
- Bachelor's or Master's degree in any discipline (Preferred: Data Science, Statistics, Actuarial Science, Computer Science, or related field).
- 36 years of experience in data analytics, preferably within the insurance or financial services industry.
- Experience with insurance systems (policy administration, claims management, CRM) is highly desirable.
- Strong analytical and problem-solving skills with attention to detail.
- Proficiency in SQL, Python/R, and data visualization tools (Power BI).
- Understanding of insurance business processes: policy lifecycle, claims, underwriting, pre-approvals, call center, and customer experience metrics.
- Knowledge of statistical techniques (regression, classification, clustering) and predictive modeling.
- Strong communication skills to present findings to both technical and non-technical stakeholders
