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The Actuarial Platform Tester is responsible for executing structured testing activities across actuarial and financial platforms. Working within the test team under the direction of the Test Lead, this role ensures test cases are executed thoroughly, defects are clearly documented, and test evidence meets audit and governance standards. The role operates with an AI-first mindset to improve testing efficiency and insight. The candidate will have responsibilities across the following functions: Test Execution: Execute test cases for SIT, UAT, regression, and release validation in line with the test plan.Follow defined test scope, entry/exit criteria, and acceptance thresholds as set by the Test Lead.Document test results accurately and completely in the agreed test management tool.Raise and log defects clearly with full reproduction steps, evidence, and severity classification.Retest defect fixes and confirm resolution before sign-off. Defect Management: Log all defects with sufficient detail for developers to reproduce and investigate.Track defect status and escalate blockers promptly to the Test Lead.Participate in defect triage meetings, providing clear and factual test observations.Maintain up-to-date test execution status in reporting dashboards as directed. Actuarial and Data-Focused Testing: Execute validation of actuarial calculation outputs, projections, and financial data against expected results.Perform data comparison testing across input files, calculation outputs, and reports.Work with actuarial SMEs to understand expected outputs and flag deviations clearly.Ensure test evidence for actuarial changes is complete, traceable, and audit-ready. AI-First and Continuous Improvement: Apply AI tools (e. g., copilots, test accelerators) to support test case execution, data analysis, and defect reporting.Use AI as an assistant, applying professional judgement and validating outputs before adoption.Actively contribute ideas to improve testing processes, standards, and tooling.Participate in retrospectives and apply learning to improve execution quality. Documentation and Governance: Ensure all test execution evidence is documented, traceable, and meets internal control expectations.Maintain test evidence in line with audit and regulatory requirements.Follow agreed naming conventions, version control, and evidence storage standards. Requirements: Minimum 5 years of experience in testing or quality assurance roles for IT platforms.Experience executing test cases across functional, regression, and integration test phases.Experience in data-heavy, financial, or enterprise IT environments is preferred.Demonstrated attention to detail and structured approach to test documentation. Technical Skills: Ability to read and understand SQL queries for data validation purposes.Experience with at least one test management tool (e. g., Azure DevOps Test Plans, Jira, ALM).Basic scripting or data manipulation (e. g., Excel, SQL, or Python) for test data preparation is an advantage.Familiarity with modern data or cloud platforms is a plus. AI and Mindset: Practical exposure to AI-assisted tools (e. g., copilots, test accelerators) is an advantage.Demonstrates curiosity, a learning mindset, and openness to adopting new ways of working.Willing to upskill in AI-assisted testing practices as part of the team's evolution. Professional Skills: Strong attention to detail and structured approach to test execution and documentation.Clear written communication, able to document defects and test results precisely.Collaborative team player who communicates blockers and progress clearly and promptly.Accountable, reliable, and self-organised in managing assigned test tasks.Bachelor's degree in Information Technology, Engineering, Mathematics, Finance, or a related field (or equivalent practical experience). Good to Have: Strong test execution discipline.Clear and precise defect documentation.Data validation experience (SQL, file comparison).Collaborative team contributor.Willingness to adopt AI-assisted testing tools. Nice to Have: Test automation experience.Experience in actuarial or risk platforms.Python scripting for data analysis.Cloud or Databricks platform exposure.CI/CD or DevOps testing experience. .