Actuarial Business Analyst

Minimum RequirementsEssential:Degree or Honours in Actuarial Science with a solid grounding in actuarial techniques and methodologies (e.g., risk modelling, claims prediction, survival analysis)7+ years experience in the insurance or financial services industry, with a focus on actuarial analysis and the application of machine learning to solve actuarial problemsProven expertise in building and deploying actuarial models (pricing, reserves, claims forecasting) combined with machine learning techniques to enhance decision-makingStrong experience in claims modelling, survival analysis, and the application of predictive analytics to real-world actuarial problemsLeadership experience in managing or mentoring a team of actuarial professionals and data scientists to deliver complex analytics solutionsProficiency in BI tools (e.g., Power BI, Tableau, Qlik Sense) for translating model outputs into business-friendly visualizationsExcellent communication skills with the ability to convey complex technical findings in clear, actionable terms to non-technical stakeholdersPreferred:Hands-on experience with Python, R, SQL, and cloud platforms (e.g., Snowflake, AWS, or Azure) for model development and deploymentExperience working with large datasets and building scalable data pipelines to support actuarial and machine learning modelsAbility to shape and prioritize both technical and business requirements, balancing actuarial rigor with business acumenStrong understanding of data-driven decision-making frameworks, especially in actuarial and insurance contextsExpectationsDirect & CultivateLead, mentor, and develop a team of Data Scientists to deliver high-impact solutions using both actuarial methodologies and advanced machine learning techniquesCultivate a collaborative, high-performance culture that encourages innovative problem-solving and data-driven decision-makingEnsure team members have the skills, resources, and support to push the boundaries of what's possible in actuarial and data science modellingDesign & DeliverOversee the design, testing, and deployment of actuarial models (including pricing, claims reserving, and survival models) alongside machine learning models to solve critical business problemsCombine actuarial science principles with advanced statistical modelling and machine learning algorithms to create highly effective, actionable solutionsMeasure, track, and communicate the commercial impact of models, ensuring clear business outcomes from every projectContinuously evaluate and refine model accuracy, relevance, and alignment with shifting business prioritiesIntegrate Tech & OperationsAct as the critical point of contact between the data scientists, and business stakeholders, ensuring alignment of business goals with technical deliverablesTranslate complex actuarial and machine learning concepts into clear, actionable insights for senior leadership, ensuring data-driven decisions are well understood across the organizationLead the integration of actuarial model outputs into the day-to-day operations, driving operational change and ensuring model adoption at all levels of the businessEnhance PerformanceGather and document detailed requirements for actuarial analytics projects, ensuring both technical and business needs are understood and addressedPromote the use of best practices in actuarial modelling, data science techniques, and machine learning deployments, striving for continuous improvement and innovationIdentify and implement opportunities for process improvements, ensuring the models are optimized and the business is maximizing the value of dataSalary StructureNegotiable Basic SalaryIncentivesBenefits(Only suitable candidates will be shortlisted and contacted within 14 days)