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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in data analysis within the insurance sector, leveraging strong SQL skills and familiarity with actuarial concepts to enhance data quality and usability. Capable of translating complex data findings into actionable insights for diverse stakeholders while fostering collaboration across teams.
Highest-signal resume keywords
Data AnalysisSQL ProficiencyActuarial Concepts FamiliarityCross-Divisional CollaborationCommunication Skills
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data AnalysisSQLPythonRActuarial ConceptsData GovernanceAnalytical ProcessesPricing MetricsData Quality ImprovementData Issue Investigation
Soft Skills
CommunicationCuriosityRelationship BuildingProblem SolvingSelf-Starting Drive
Industry Keywords
InsuranceFinancial ServicesData-Intensive EnvironmentPricingReservingPortfolio ManagementData AnalyticsBusiness Impact AssessmentStakeholder EngagementContinuous Improvement
Tech Stack
Tools & technologiesPythonSQL
About the role
Key responsibilities & impact- Support the development and continuous improvement of Ki’s digital underwriting capability
- Enhance the quality, credibility, and usability of data across the actuarial function
- Partner with Commercial Data, Reserving, and Portfolio Management teams to investigate data issues and improve analytical processes
- Lead and contribute to cross-divisional data analytics initiatives improving pricing metrics and actuarial outputs
- Support PLR and RARC deep-dive analysis and PMDR reviews, including investigating data issues and bugs
- Scope problems, assess severity and business impact, and propose solutions
- Identify data gaps and improvement areas with the Commercial Data squad, providing actuarial business context for roadmap prioritisation
- Develop and maintain understanding of data relationships across Pricing, Reserving, and Portfolio Management
- Act as a knowledge resource for the broader organisation
- Produce accurate, insightful analysis supporting business understanding and commercial decision-making
- Translate complex data findings into actionable insights for technical and non-technical stakeholders
- Support continuous improvement of data governance, analytical processes, and reporting
- Build cross-business relationships to facilitate collaboration, knowledge sharing, and strategic delivery
Requirements
What you’ll need- Proven experience as a data analyst, ideally within insurance, financial services, or a similarly data-intensive environment
- Familiarity with actuarial concepts and insurance data — exposure to pricing, reserving, or portfolio management workflows is highly desirable
- Strong SQL skills and comfort working with large, complex datasets; Python or R a plus
- Ability to investigate ambiguous data problems independently, form hypotheses, and communicate findings clearly
- Strong written and verbal communication skills
- Ability to communicate complex technical concepts to different audiences
- Curiosity and enthusiasm to challenge existing practices and bring fresh ideas
- Ability to build effective working relationships within the team and across the wider business
- Self-starting drive to succeed and deliver work to achieve goals and meet deadlines
Benefits
Comp & perks- Highly competitive remuneration and benefits package
- Remuneration and benefits package kept under constant review
- Recognition and rewards for extraordinary effort by teams or individuals
- Initial recruiter screening call
- Interview with hiring manager
- Technical Interview
- Values Interview