Insurers in Singapore are hiring mainly for data and analytics, AI and machine learning with strong governance, cyber security and cloud, core insurance systems, and the data skills behind IFRS 17 reporting. Much of this demand is shaped by MAS rules on technology risk and AI, so candidates who pair technical skills with insurance and regulatory knowledge stand out.
Why insurers’ tech hiring looks different
An insurer is not a tech start-up. Its systems hold decades of policy data, its models feed regulatory capital and reserving, and it is supervised by the Monetary Authority of Singapore (MAS). That means the most valued tech people are those who can build new things and also explain risk, controls and data lineage to auditors and regulators.
Two public frameworks are useful for seeing what the industry asks for:
- The Skills Framework for Financial Services, developed by IBF, MAS, SkillsFuture Singapore and Workforce Singapore, covers 157 job roles across six tracks, one of which is Digital and Data Analytics. Its named emerging skills include cybersecurity, data collection and analysis, risk management, digital literacy and user experience design.
- IBF’s Future-Enabled Skills are Data Fluency, Digital Literacy, Digital Risk and Governance, Generative AI, and Sustainable Finance.
The six skill areas in demand
1. Data engineering and analytics
Pricing, claims, distribution and finance all depend on clean, well-governed data. Insurers hire data engineers who can build pipelines from legacy policy administration systems, and analysts who can turn that data into decisions. Useful skills include SQL, Python, cloud data platforms, data modelling and data quality controls. Data fluency, which IBF describes as reading, interpreting and applying data to make decisions, is now expected well beyond the data team.
2. AI and machine learning, with governance
Insurers use machine learning in pricing, fraud detection, claims triage and customer service, and are testing generative AI for documents and service. Governance is the differentiator. On 13 November 2025 MAS published a consultation paper on proposed Guidelines on AI Risk Management for all financial institutions, covering oversight of AI risk, AI life-cycle controls, and the capabilities and capacity firms need to use AI. It builds on MAS’s earlier FEAT principles (Fairness, Ethics, Accountability and Transparency). Candidates who can show model validation, explainability, bias testing and human oversight are in a stronger position than those who only build models.
3. Cyber security and technology risk
The MAS Technology Risk Management Guidelines, revised in January 2021, apply across the financial institutions MAS regulates. They address cloud, application programming interfaces (APIs) and agile software development, call for cyber threat intelligence sharing and simulated cyber exercises, stress oversight of third-party providers, and expect firms to have qualified Chief Information Officers and Chief Information Security Officers. In practice this creates demand for:
- Security engineers and architects, especially for cloud environments
- Technology risk and IT audit specialists who can map controls to MAS expectations
- Third-party and outsourcing risk managers
- Incident response and security operations staff
4. Cloud and platform engineering
Moving workloads to the cloud is now routine, but in a regulated insurer every migration has to satisfy technology risk, outsourcing and data protection expectations. Engineers who understand infrastructure as code, identity and access management, and resilience testing, and who can document controls clearly, are hired across life and general insurers.
5. Core insurance systems and integration
Policy administration, claims and billing platforms sit at the heart of every insurer. Business analysts, solution architects and developers with experience of core system replacement, product configuration and API integration with distribution partners remain in steady demand. This work often runs as large programmes, which is also why contract programme managers and business analysts are hired on project terms.
6. Finance and actuarial data (IFRS 17)
Insurers in Singapore apply IFRS 17 (adopted locally as FRS 117 and SFRS(I) 17) for annual periods beginning on or after 1 January 2023, as noted in IRAS’s e-Tax Guide on the taxation of insurers. The standard is data-heavy, so insurers need people who connect actuarial models, finance ledgers and reporting tools: actuarial systems specialists, finance data engineers and reporting analysts who understand both the accounting and the technology.
Roles and what they tend to ask for
| Role | Core technical skills | Insurance context that helps |
|---|---|---|
| Data engineer | SQL, Python, cloud data platforms, pipeline tools | Policy and claims data structures, data lineage for reporting |
| Data scientist or ML engineer | Python, statistics, model deployment, monitoring | Pricing, fraud or claims use cases, model governance |
| Cyber security engineer | Cloud security, identity and access, threat detection | MAS technology risk expectations |
| Technology risk manager | Control frameworks, IT audit, third-party risk | MAS TRM Guidelines, outsourcing oversight |
| Business analyst or solution architect | Requirements, process design, API integration | Core policy, claims and billing systems |
| Actuarial or finance systems specialist | Actuarial software, data modelling, reporting tools | IFRS 17, reserving and capital processes |
What these skills pay
Pay depends heavily on seniority and employer. As a cross-industry reference, the PERSOL Singapore salary guide for 2026/27, as reported by Human Resources Online, gives typical monthly base salaries of SGD 6,000 to 12,000 for AI engineers, SGD 7,500 to 14,000 for data scientists, and SGD 7,000 to 15,000 for cybersecurity managers. These are not insurance-specific figures, so use them as a starting point and test them against actual offers. For insurance-specific pay, see our pages on actuary salaries in Singapore and underwriter salaries in Singapore.
How to show these skills to an insurer
- Lead with outcomes. “Cut claims triage time” or “rebuilt the pricing data pipeline” means more than a list of tools.
- Show you understand control. Mention model validation, access controls, audit trails or regulatory reviews you supported.
- Learn the insurance basics. Know how premiums, claims, reserves and reinsurance flow through the business.
- Use the IBF frameworks. Map your skills to the Skills Framework language that HR teams in Singapore recognise.
- Consider adjacent paths. Analytics and catastrophe modelling can lead into broking. See how to get a job in reinsurance broking in Singapore.
How LUNOS can help
Technology is one of the seven desks at LUNOS, covering insurtech, core systems, data and product talent up to CTO level, and our Contracting and Consulting desk places programme managers, business analysts and consultants on transformation work. We work across Singapore, Malaysia and Hong Kong. If you are a tech professional considering a move into, or within, insurance, or an insurer building a data or technology team, start a conversation with LUNOS.
Frequently asked questions
Do I need insurance experience to get a tech job at an insurer in Singapore?
Not always. Strong engineers and data specialists are hired from other sectors, but some understanding of how policies, claims and reserves work helps you stand out and ramp up faster.
Which tech skill is most in demand at Singapore insurers?
Data skills underpin most of the demand, from analytics and machine learning to IFRS 17 reporting. Cyber security and technology risk are close behind because of MAS expectations.
Does MAS regulation affect tech roles at insurers?
Yes. The MAS Technology Risk Management Guidelines and the proposed AI Risk Management Guidelines shape how insurers build, run and govern their systems and models.
Are contract roles common in insurance technology?
Yes. Large core system and transformation programmes often hire programme managers, business analysts and specialists on contract or project terms.