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 solutions through its dollarDEX and Navigator platforms. The mobile-first Singlife Account – with a Singlife Debit Card – allows customers to save, spend, earn and be insured all in one app.
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, affirming its commitment to finding a better way to sustainability.
First announced in September 2020 and valued at S$3.2 billion, the merger of Aviva Singapore and Singlife was the largest insurance deal in Singapore then and created one of the largest homegrown financial services companies in the republic.
Key Responsibilities
· Collaborate with stakeholders, senior data scientists and cross-functional teams to understand business objectives and requirements.
· Conduct comprehensive data analysis and apply advanced statistical techniques to identify patterns, trends, and extract insights from large and complex datasets.
· Create visually appealing and insightful data visualizations to communicate complex findings and insights to both technical and non-technical stakeholders.
· Develop and maintain scalable data pipelines and workflows to process and analyse large volumes of data.
· Develop, validate, and maintain predictive models and algorithms tailored to specific business use cases such as customer segmentation and propensity models.
· Contribute to the design and implementation of experiments to test hypotheses and validate model performance.
· Work closely with machine learning engineers to deploy models into production and monitor their performance, providing insights and recommendations for optimization.
· Document methodologies, procedures, and findings in a clear and concise manner to ensure knowledge sharing and maintain accurate records.
· Stay abreast of emerging trends and advancements in data science and machine learning.
Requirements
Experience
· 2-5 years of experience in data science or a related field.
· Knowledge of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
· Proficiency in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and algorithm development.
· Strong programming skills in Python, R, SQL, or other programming languages.
· Deep understanding of statistical concepts and techniques, with experience applying them to real-world problems.
· Ability to visualize data, identify trends, and provide sound insights/ suggestions to internal stakeholders.
· Experience in the financial and insurance sector will be advantageous.
· Experience with AWS (Amazon Web Services) cloud services (S3, EC2, SageMaker).
· Eagerness to learn and adapt to new technologies and methodologies.
· Understanding of Generative AI methodologies, including Retrieval-Augmented Generation (RAG) and frameworks like LangChain.
Education
· Bachelor’s degree or above in Statistics, Computer Science, Mathematics, Business Analytics, Economics, or Similar or Masters in Statistics or any quantitative analytics or equivalent professional qualification.
