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.
Key Responsibilities
•Design, build, and enhance analytics reports to ensure accuracy as well as relevance for business analysis and decision making.
•Provide quality business trend analysis and diagnostics.
•Provide technical / data support to General Insurance team and the key stakeholders.
•Get involved in product pricing.
•Perform user acceptance tests on pricing related.
•Maintain effective communication with key business stakeholders.
Requirements
Experience
•1-2 years of experience participating in analytics tasks
•Experience in general insurance industry would be a plus
•Having actuarial knowledge would be a plus
Education
•Academic: Bachelor’s / Master’s degree in Statistics, Actuarial Science, Mathematics, or equivalent disciplines that focus on data analysis