Singapore, Singapore, Singapore (4 Shenton Way, SGX Center 2)
Department
Data Science and Analytics
Job posted on
Aug 11, 2025
Employee Type
Permanent - Full Time
Experience range (Years)
3 years - 5 years
Singlife is a leading homegrown financial services company, offering consumers a better way to financial freedom. Through innovative, technology-enabled solutions and a wide range of products and services, Singlife provides consumers control over their financial wellbeing at every stage of their lives.
In addition to a comprehensive suite of insurance plans, employee benefits, partnerships with financial adviser channels and bancassurance, Singlife offers investment and advisory solutions through its GROW with Singlife platform. It also offers the Singlife Account, a mobile-first insurance savings plan.
Singlife is the exclusive insurance provider for the Ministry of Defence, Ministry of Home Affairs and Public Officers Group Insurance Scheme. Singlife is also an official signatory of the United Nations Principles for Sustainable Insurance and the United Nations-supported Principles for Responsible Investment, affirming its commitment to finding a better way to sustainability.
The merger of Aviva Singapore and Singlife was announced in September 2020 and created one of the largest homegrown financial services companies in Singapore in a deal valued at S$3.2 billion. It was the largest insurance deal in Singapore at the time. Singlife was subsequently acquired by Sumitomo Life in March 2024, one of Japan’s leading life insurers, which valued Singlife at S$4.6 billion, making the transaction one of the largest insurance deals in Southeast Asia.

EXPERIENCE:

• 3–5 years of experience in data governance, data analysis, or data management within the insurance or financial services sector.
• Strong understanding of insurance business concepts across Life, Health, Group, and General Insurance products and operations.
• Strong knowledge of data modeling (conceptual, logical, and physical), relational databases.
• Solid SQL skills and experience working with metadata management or data catalog tools.
• Proven ability to translate complex business requirements into scalable and efficient data models aligned with enterprise data architecture standards.
• Proven track record of collaborating with business stakeholders and technical teams to gather and translate data requirements into actionable data solutions.
• Proven experience participating in or leading data transformation projects, including data migration, integration, cleansing, and restructuring to support improved data quality, governance, and analytics outcomes.
• Hands-on experience or strong understanding of Generative AI technologies and their applications to automate data processes, improve data modeling, and innovate data products within the organization.
• Knowledge/experience with Oracle Cloud, Snowflake, AWS S3, Airflow will be advantageous

EDUCATION:

• Bachelor’s degree in Information Systems, Computer Science, Data Management, Business Analytics, Actuarial Science, or a related discipline.

• Support the implementation of data governance policies, standards, and frameworks across all insurance Lines of Business (e.g., Life, Health, General, Group).
• Assist in the development and maintenance of conceptual, logical, and physical data models, ensuring alignment with business definitions and enterprise data architecture.
• Support the development of core data models for the Data Analytics Business Partner team to facilitate effective implementation and delivery of data products.
• Collaborate with system owners, and data owners, data stewards to gather data requirements and translate them into clear data mapping documents and specifications that guide data engineers in implementation, ensuring alignment between business needs and data solutions
• Contribute to the maintenance of data dictionaries, data catalogs, and data lineage documentation to support regulatory compliance, internal reporting, and cross-LOB data integration.
• Perform basic data profiling and quality checks to support data quality initiatives and identify anomalies in critical data elements (e.g., customer, policy, claims, coverage).
• Help track and report data quality issues, support remediation plans, and monitor adherence to data governance processes.
• Identify and implement opportunities to automate business workflows, including data quality checks, metadata management, reporting processes, and cross-functional data operations, to improve efficiency and reduce manual effort.
• Explore and support the integration of Generative AI technologies to enhance data modeling, data governance, automation, and data product innovation within the Data Analytics function.