Data Analytics & Governance

Support the Data Intelligence and Reporting Manager with setting the data provisioning and democratization strategic direction and roadmap. Ensure that data intelligence and reporting projects align with organizational goals.

Responsibilities

• 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 dashboards, 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.

Qualifications

• Bachelor's or Master's degree in any discipline (Preferred: Data Science, Statistics, Actuarial Science, Computer Science, or related field).
• 3-6 years of experience in data analytics, preferably within the insurance or financial services industry.
• Insurance systems (policy administration, claims management, CRM) experience 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.