Data Analyst

About the role

AIA Investment Management is seeking a Data Analyst to join its Data Science and Analytics team. The role acts as a central coordinator for data sourcing and management, working with internal stakeholders and data providers to collect, collate, cleanse, transform and validate data for analytical and reporting purposes. It also supports data governance and quality standards and contributes to the team's analytics capabilities.

Key responsibilities

• Coordinate with business users, data owners, technology teams and external data providers to obtain data needed for analysis and reporting, and follow up on requests and delivery status.
• Identify suitable data sources and document ownership, file locations, formats, refresh frequency and key business definitions.
• Collect and consolidate data from spreadsheets, documents, emails, system extracts and other structured or unstructured inputs, and standardise it into consistent templates.
• Convert unstructured or semi-structured information into structured datasets while preserving source details and traceability.
• Perform routine data extraction, transformation and loading using tools such as Excel, SQL or Python, and clean data by resolving formatting differences, duplicates, missing values and inconsistent labels.
• Prepare repeatable data processing steps and maintain simple scripts, queries, templates or workflows under the guidance of senior team members.
• Run completeness, accuracy, consistency, validity and reconciliation checks, investigate data exceptions and work with data owners to resolve issues.
• Maintain data quality checklists, issue logs, validation evidence and records of corrections or assumptions.
• Maintain data dictionaries, process notes, file inventories, data lineage records and operating instructions, and share knowledge within the team.

Required profile

• 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 in data sourcing, preparation, ETL and/or data quality management.
• Strong attention to detail, ability to work accurately with large datasets, maintain documentation and meet agreed timelines.
• Good written and verbal communication skills and a proactive learning mindset.
• Exposure to investment management, financial data, reporting, cloud data platforms or data visualisation tools is advantageous but not required.

Required skills

• Proficiency in Microsoft Excel.
• Exposure to SQL, Python, Power Query or similar data preparation tools is advantageous.
• Basic understanding of data cleansing, data transformation, ETL processes and data quality checks.