AI
AiaData Analyst (AIA Investment Management)
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Before you apply
LocationSG-AIA Tower
Typefull-time
SeniorityEntry
DepartmentData Science and Analytics
Company size10,000+ people
PostedOct 30, 2026 · 5d ago
Verified live1d ago
Start building a career with purpose.
At AIA, your perspective, curiosity and ideas can contribute to our Purpose of helping millions of people live Healthier, Longer, Better Lives. Across our diverse markets, you will learn through meaningful work, collaborate with experienced colleagues and build practical skills as you turn fresh ideas into positive outcomes and a more sustainable future for our customers and communities.
Join us to explore new possibilities, grow through real experiences and start making an impact across Asia.
About the Role
Join us as Data Analyst at AIA Investment Management!
At AIA Investment Management, we believe in creating long-term value for our clients and communities. We are seeking a Data Analyst to join our Data Science and Analytics team. In this role, you will serve as a central coordinator for data sourcing and management, working closely with internal stakeholders and data providers to collect, collate, cleanse, transform, and validate data for analytical and reporting purposes. You will be responsible for ensuring the accuracy, consistency, and integrity of data, conducting data quality checks, and supporting the timely delivery of high-quality data used in investment analysis, reporting, and decision-making processes. Partnering across functions, you will help strengthen data governance and quality standards, while building deep expertise in investment data and contributing to the development of the team’s analytics capabilities.
Key Responsibilities
As part of our high-performing team, you will be responsible for:
1.
Data Sourcing and Coordination
•
Coordinate with business users, data owners, technology teams, and external data providers to obtain data required for analysis and reporting.
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Follow up on data requests, clarify data requirements, track delivery status, and highlight delays or gaps promptly.
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Identify suitable data sources and document source ownership, file locations, formats, refresh frequency, and key business definitions.
2.
Data Collation and Preparation
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Collect and consolidate data from multiple sources, including spreadsheets, documents, emails, system extracts, and other structured or unstructured inputs.
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Organise and standardise data into consistent templates and structures that can be used by the Data Science and Analytics team.
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Convert unstructured or semi-structured information into structured datasets while preserving source details and traceability.