I am a Data & Insight Analyst with experience delivering customer-led analytics within regulated environments, including insurance and healthtech. My work focuses on analysing complex customer complaints and operational data to identify root causes, behavioural patterns, and systemic gaps that impact customer outcomes and business performance.

In my current role within the travel insurance sector, I work extensively with complaint and feedback data, investigating issues related to auto-renewals, medical disclosures, waiting lists, policy awareness, and agent behaviour. My analysis supports operational and leadership teams in refining processes, improving communication, and reducing avoidable customer dissatisfaction.

Previously, I contributed to the conceptual development of secure digital workflows within a healthtech environment, exploring how blockchain-based approaches can enhance data integrity, transparency, and trust in systems handling sensitive information.

I am particularly interested in building analytical frameworks that go beyond reporting, enabling data-driven decision-making, accountability, and measurable service improvement.

• Project Blockchain Audit & Transparency Systems : A research-driven blockchain system that provides tamper-evident audit trails for critical business decisions. The project uses a hybrid on-chain/off-chain architecture, cryptographic integrity verification, and transparency dashboards to support traceability and trust in regulated environments.

• Designing complaint and decision analytics that inform operational and policy-level improvements
• Identifying preventable customer harm through root-cause and lifecycle analysis
• Supporting leadership teams with evidence-based insights to improve fairness, clarity, and trust
• Building analytical frameworks that move beyond reporting to accountability and action

• Customer Complaints Insight & Root Cause Analysis
• Auto-Renewal & Policy Lifecycle Analytics
• Decision-Focused Reporting for Non-Technical Stakeholders
• Trust, Transparency & Data Integrity in Digital Systems

• Decision & Customer Intelligence — end-to-end analysis of complaints, customer behaviour, and service outcomes in regulated environments
• Data Modelling & Analytical Design — structuring datasets, lifecycle models, and metrics for audit-ready insights
• Business Intelligence & Insight Delivery — stakeholder-ready dashboards and evidence-based recommendations
• Integrity, Transparency & Trust Analytics — auditability, traceability, and verification-focused system design
• Statistical Analysis & KPI Architecture — defining measurable performance and risk indicators
• Automation & Analytical Tooling — reproducible analysis and process efficiency

• Translating complex analysis into decision-ready narratives for non-technical stakeholders
• Structuring analytical frameworks adopted across investigations and reviews
• Balancing regulatory, customer, and operational considerations in insight delivery