DATA ANALYST - Python, SQL and AI

ABOUT THE ROLE

We are seeking a Data Analyst to support the Operations team across multiple geographies. This role is central to how the function monitors performance, identifies trends and makes decisions — and will work directly with senior leadership to deliver actionable insights from complex, multi-system data environments.

KEY RESPONSIBILITIES

BAU Reporting and Data Management

• Produce and maintain regular BAU reports covering claims volumes, financials, headcount and performance metrics across APAC markets.
• Manage and reconcile data from multiple source systems, geographies and business lines, ensuring accuracy and consistency.
• Identify, investigate and resolve data discrepancies, working with local market teams and IT as needed.
• Maintain data documentation, version control and audit trails for all reporting outputs.

Ad Hoc Analysis

• Respond to ad hoc data requests from senior leaders, including market-level deep dives, financial banding analysis and portfolio reviews.
• Build and run queries across relational databases and data warehouses to extract and manipulate large datasets.
• Translate ambiguous business questions into structured analytical frameworks with clear outputs.

Dashboard Development

• Design, build and maintain interactive dashboards and visualisations for operational and leadership audiences.
• Iterate on existing reporting tools based on stakeholder feedback, ensuring outputs remain relevant and usable.
• Ensure dashboards are scalable across markets and can be updated efficiently as data sources evolve.

AI and Emerging Technology

• Apply AI and machine learning tools to enhance data processing, pattern recognition and predictive analytics within the claims function.
• Identify opportunities to embed AI-assisted automation into existing reporting and analytical workflows, reducing manual effort and improving speed to insight.
• Collaborate with the broader Transformation agenda to pilot and scale AI use cases, including natural language querying, anomaly detection and document summarisation.
• Stay current with developments in AI tooling relevant to data and operations, and bring forward practical recommendations for adoption.

Continuous Improvement

• Proactively identify gaps in current data coverage or reporting processes and propose solutions.
• Automate repetitive reporting tasks to improve turnaround time and reduce manual error.

SKILLS AND EXPERIENCE

Essential

• 8-12 years in a data analyst or similar role, preferably in financial services, insurance or a similarly complex operational environment.
• Proficiency in Python (pandas, openpyxl, matplotlib or similar) or equivalent scripting/automation skills.
• Strong SQL skills with experience querying multi-table relational databases.
• Experience working with data from multiple systems, geographies or business units.
• Proven ability to identify and resolve data quality issues with minimal supervision.
• High proficiency in Excel, including pivot tables, complex formulas and data modelling.
• Experience building dashboards using tools such as Power BI, Tableau or equivalent.
• Practical experience using AI tools (e.g. LLMs, Copilot, AI-assisted coding or analytics platforms) to improve analytical output or workflow efficiency.

Desirable

• Exposure to claims, actuarial or insurance data.
• Experience working in or with APAC markets.
• Familiarity with PowerPoint automation or report generation via Python.
• Understanding of financial reporting, including expense management or claims financials.
• Experience with machine learning concepts or predictive modelling.

QUALIFICATIONS

Essential

• Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Economics or a related quantitative discipline.

Desirable

• Postgraduate qualification in a relevant field.
• Professional certification in data or analytics (e.g. Microsoft Power BI Data Analyst, Google Data Analytics Certificate, AWS Certified Data Analytics).
• Certification or coursework in AI or machine learning (e.g. Coursera ML Specialisation, DataCamp AI Fundamentals).

ATTRIBUTES

• Proactive self-starter who identifies problems and acts before being asked.
• Highly organised, able to manage multiple competing priorities to tight deadlines.
• Comfortable operating in ambiguity and translating incomplete briefs into structured work.
• Strong communicator who can present data clearly…