Actuarial Analyst, Experience Studies & Business Process Management

• Support life and health experience studies, including mortality, morbidity, lapse and claims analysis.
• Perform data validation, exposure calculations, actual-versus-expected analysis, and investigation of experience trends.
• Apply actuarial and statistical techniques to support assumption reviews and experience analysis.
• Interpret and communicate study findings through reports, presentations and visualisations.
• Develop and maintain actuarial analytics and experience study workflows using Databricks, SQL, Python and PySpark.
• Prepare, reconcile and analyse policy, exposure and claims data, investigating data quality issues and their impact on results.
• Support the enhancement and modernisation of actuarial tools, models and analytical processes.
• Collaborate with actuarial, business and technology teams to deliver scalable and controlled analytical solutions.
• Identify opportunities to improve actuarial processes through automation, workflow optimisation and standardisation.
• Support process improvement initiatives, including process mapping, testing, implementation and user adoption.
• Explore and assess AI and machine learning applications to enhance actuarial analysis and operational efficiency.
• Ensure solutions comply with applicable governance, data privacy, information security and AI risk management requirements.

Your Profile

• Degree in Actuarial Science, Mathematics, Statistics, Computer Science or another quantitative discipline.
• Progress towards Fellowship of a recognised actuarial qualification.
• Relevant actuarial experience within life and health insurance or reinsurance.
• Experience in experience studies, assumption setting, pricing, valuation or related actuarial functions.
• Strong technical skills in Databricks, SQL and Python; experience with Spark/PySpark is advantageous.
• Experience working with large and complex datasets and analytical workflows.
• Solid understanding of statistical methods and the ability to apply actuarial judgement to business problems.
• Experience developing, evaluating or implementing AI and/or machine learning solutions in a business environment.
• Strong analytical, problem-solving and communication skills.
• Ability to explain technical concepts to both technical and non-technical stakeholders.
• Ability to work independently while collaborating effectively across teams and locations.

Nice to Have

• Experience conducting life and health experience studies across multiple products, portfolios or markets.
• Knowledge of machine learning, credibility theory or advanced statistical techniques.
• Experience with Databricks capabilities such as Delta Lake, Unity Catalog, Workflows or MLflow.
• Exposure to large language model (LLM) applications, retrieval-augmented generation (RAG), API integration or natural language analytics.
• Experience in process improvement methodologies, workflow automation or change implementation.
• Relevant Databricks, analytics or cloud certifications.