At AIA we’ve started an exciting movement to create a healthier, more sustainable future for everyone.
It’s about finding new ways to not only better people's lives, but to better the communities and environments we live in. Encompassing our ambition of helping a billion people live Healthier, Longer, Better Lives by 2030.
And to get there, we need ambitious people who believe in playing an important part in shaping that future. People seeking unmatched career and personal growth opportunities, who are driven to work with, and learn from some of the most inspiring and supportive leaders in the business.
Sound like you? Then read on.
About the Role
Join us as Data & Analytics Analyst at AIA Investment Management!
The Data & Analytics Analyst is responsible for developing, maintaining, and enhancing data, analytics, reporting, and automation solutions that support Investment Management, Front Office, and Middle Office functions. The role enables data-driven decision-making by delivering high-quality analytical datasets, insightful reporting, scalable data products, and automation capabilities that improve operational efficiency, strengthen data quality, and support business performance.
Working closely with business stakeholders and technology partners, the incumbent combines analytics engineering, reporting, automation, and data management expertise to translate complex business requirements into practical analytical solutions. The role supports a broad range of business needs, including management reporting, investment analytics, KPI monitoring, regulatory reporting, and business process optimization, while ensuring the integrity, reliability, and accessibility of data across the organization.
The Data & Analytics Analyst makes a meaningful contribution to the firm's data-driven culture by developing reusable data assets, automated workflows, and self-service reporting capabilities that enhance operational effectiveness and management decision-making. In addition to supporting day-to-day analytical and reporting requirements, the role contributes to the organization's long-term analytics, automation, and AI enablement agenda by leveraging emerging technologies, including AI-assisted tools, to build scalable analytical products and continuously improve reporting, automation, and data management capabilities.
Responsibilities
1. Analytics Engineering & Data Management
- Develop, maintain, and enhance analytical datasets, data models, and transformation workflows supporting investment and operational reporting requirements.
- Support the ingestion, integration, validation, and documentation of investment and business data while ensuring datasets are scalable, reusable, and aligned with analytical standards.
- Contribute to the maintenance of metadata, documentation, and data lineage.
- Support the development of analytical datasets and data products that enable investment decision-making, portfolio analysis, and performance monitoring across both Front Office and Middle Office functions.
2. Data Quality & Controls
- Implement data quality controls, reconciliation checks, and validation processes to ensure reliability and accuracy of analytical outputs.
- Investigate data quality issues, reporting anomalies, and process exceptions while supporting documentation requirements and reporting definitions.
3. Automation & AI Enablement
- Design, develop, and maintain Python-based automation solutions that improve operational efficiency and reduce manual effort. Identify opportunities to streamline processes through workflow automation and support the adoption of AI-enabled productivity, reporting, and analytics solutions where appropriate.
- Support experimentation and adoption of AI-enabled analytics, natural language querying, data assistants, and productivity tools to enhance analytical efficiency, insight generation, and user experience.
4. Reporting & Analytics Delivery
- Develop and maintain Power BI dashboards, management reports, and analytical solutions that provide timely and accurate insights to business stakeholders.
- Deliver recurring and ad-hoc analytics, support KPI reporting requirements, and contribute to self-service analytics capabilities through the creation of curated analytical datasets and reporting assets.
5. Stakeholder Engagement & Project Delivery
- Collaborate with stakeholders across Investment Management, Middle Office, Operations, Risk, ESG, and Technology teams to gather business requirements, support testing activities, and assist with solution implementation.
- Contribute to project delivery, documentation, knowledge transfer, and continuous improvement initiatives.
Requirements
- Degree in Data Science, Computer Science, Information Systems, Engineering, Mathematics, Statistics, Finance, or related discipline.
- Min 1 year of relevant experience in analytics engineering, business intelligence, automation, data analytics, or related disciplines.
- Strong proficiency in Python, SQL, Power BI, and Microsoft Excel.
- Experience working with data transformation, ETL/ELT concepts, and data quality validation processes.
- Experience developing dashboards, reporting solutions, and analytical datasets.
- Strong analytical, problem-solving, and stakeholder engagement skills.
- Ability to translate business requirements into practical analytics and reporting solutions.
- Experience with Azure Databricks, Unity Catalog, Power Automate, REST APIs, Git, cloud data platforms, or AI-assisted development tools is advantageous.
- Exposure to asset management, investment operations, performance analytics, portfolio analytics, AUM reporting, ESG reporting, risk analytics, or investment data management is advantageous.
Believe in better with AIA. If you work at AIA, you play an important part in this movement. Which is why we give you every opportunity to learn, grow and shape your career - your way!
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Build a career with us as we help our customers and the community live Healthier, Longer, Better Lives.
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