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Mid-level data analytics role with popular title, metro location, and broad skill requirements drives high competition.
Actuarial and heavily audited financial services context makes background fit highly industry-specific.
Explicit 6–10 years, domain-specific tech and audited financial services experience increase filtering strictness.
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Operate, maintain, and update BAU data pipelines that validate, transform, and enrich actuarial policyholder data for modelling and assumption setting.
Ensure data integrity through validation, quality checks, governance, and timely issue resolution in collaboration with stakeholders.
Produce accurate reports, dashboards, and documentation supporting auditability and operational resilience within agreed timelines.
6-10 years of relevant Data Analytics experience, preferably in Financial Services or a similar heavily audited environment.
Bachelor’s or Master’s Degree; Data Analyst certifications advantageous but not mandatory.
Proficiency in Excel (advanced formulas, pivot tables, Power Query), Power BI, Python/PySpark, and understanding of data pipelines and data governance.
Ability to handle audit queries and maintain documentation for controls and evidence to support operational resilience.
Experienced data analyst with strong analytical and data transformation skills specifically for actuarial or financial data.
Capable of working independently within established frameworks and managing workload with strong attention to detail and compliance.
Effective communicator able to translate complex data insights for technical and non-technical stakeholders, supporting cross-functional collaboration.