Data Analyst (AIA Investment Management)

AIA (Vietnam) Life Insurance; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

AIA Investment Management is seeking a Data Analyst to join the Data Science and Analytics team. You will coordinate data sourcing, prepare and standardize data, and support data quality checks to ensure accurate investment analysis and reporting.

The role involves working with internal stakeholders and data providers, performing basic ETL using Excel/SQL/Python, and contributing to data governance and analytics capabilities within the team.

Qualifications

• Bachelor's degree or diploma in data-related field with internship or project experience involving data sourcing, ETL or data quality.
• Proficiency in Microsoft Excel; exposure to SQL, Python, Power Query or similar data preparation tools would be advantageous.
• Basic understanding of data cleansing, data transformation, ETL processes, and data quality checks, with strong analytical skills.
• Strong attention to detail and ability to work with large datasets, with good documentation practices.
• Good written and verbal communication skills, and ability to engage data owners and stakeholders across teams.
• Willingness to learn new tools and data processes; exposure to investment management is a plus.

Responsibilities

• Data Sourcing and Coordination with data owners, technology teams, and external data providers.
• Data Collation and Preparation: consolidate data into consistent templates and structures.
• Data Cleaning and ETL: perform data extraction, transformation, and loading using Excel, SQL, or Python.
• Data Quality Checks and Issue Resolution: run checks and resolve data issues with owners.
• Documentation and Team Support: maintain data dictionaries, process notes, and data lineage.

Skills

Attention to detail

Analytical skills

Communication skills

Learning mindset

Problem-solving

Education

Bachelor's degree / Polytechnic diploma in Data Science or related

Tools

Excel

SQL

Python

Power Query

Job description

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

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.
   Follow up on data requests, clarify data requirements, track delivery status, and highlight delays or gaps promptly.
   Identify suitable data sources and document source ownership, file locations, formats, refresh frequency, and key business definitions.
2. Data Collation and Preparation
   Collect and consolidate data from multiple sources, including spreadsheets, documents, emails, system extracts, and other structured or unstructured inputs.
   Organise and standardise data into consistent templates and structures that can be used by the Data Science and Analytics team.
   Convert unstructured or semi-structured information into structured datasets while preserving source details and traceability.
3. Data Cleaning and ETL
   Perform routine data extraction, transformation, and loading activities using tools such as Excel, SQL, or Python.
   Clean and standardise data by resolving formatting differences, duplicates, missing values, inconsistent labels, and other common data issues.
   Prepare repeatable data processing steps and maintain simple scripts, queries, templates, or workflows under guidance from senior team members.
4. Data Quality Checks and Issue Resolution
   Perform completeness, accuracy, consistency, validity, and reconciliation checks before data is used for analysis or reporting.
   Investigate data exceptions, compare results with source records, and work with data owners to resolve identified issues.
   Maintain data quality checklists, issue logs, validation evidence, and clear records of corrections or assumptions.
5. Documentation and Team Support
   Maintain data dictionaries, process notes, file inventories, data lineage records, and operating instructions.
   Provide timely progress updates, communicate issues clearly, and support knowledge sharing within the team.
   Learn new data tools, business concepts, and working methods as required, and apply feedback to improve the quality and efficiency of work.

Minimum Requirements

• Bachelor's degree or Polytechnic diploma in Data Science, Data Analytics, Computer Science, Information Systems, Engineering, Mathematics, Statistics, Finance, or a related discipline, with relevant internship, academic project, or practical experience involving data sourcing, data preparation, ETL, and/or data quality management.
• Proficiency in Microsoft Excel; exposure to SQL, Python, Power Query, or similar data preparation tools would be advantageous.
• Basic understanding of data cleansing, data transformation, ETL processes, and data quality checks, coupled with strong analytical and problem-solving skills to investigate discrepancies and validate information against source data.
• Strong attention to detail, with the ability to work accurately with large datasets, maintain proper documentation, follow established processes, and meet agreed timelines.
• Good written and verbal communication skills, with the professionalism and confidence to engage data owners and stakeholders effectively and work collaboratively across teams.
• A proactive learning mindset, with the willingness to learn new tools, business concepts, and data processes.
• Exposure to investment management, financial data, reporting, cloud data platforms,