Source description
About the role
Technical Skills
Strong general insurance domain knowledge, ideally commercial insurance, workers' compensation or general insurance actuarial.
Deep knowledge of the full data lifecycle with experience hands on building data capture, data pipelines, reporting and statistical/ML models ideally end-to-end.
Knowledge of data and analysis languages: SQL, SAS, Python, R, PL/SQL, PG/PL, VBA or Java.
Uses AI regularly and appropriately to accelerate delivery utilisation across coding assistants for pipelines and queries, drafting documentation, speeding up analysis and prototyping models.
Can evaluate and integrate AI/ML capabilities into insurance workflows (e.g. risk scoring, document extraction, anomaly detection) and assess output for quality, bias and compliance.
Practical knowledge of business intelligence and reporting platforms such as Tableau, Power BI, SAS Visual Analytics, Qlik or Hex.
Practical knowledge of data platforms, warehouses and cloud tooling e.g. Snowflake, Databricks, dbt, Airflow, Postgres, Redshift, Microsoft SQL Server, Oracle or DB2, AWS, Google Cloud Platform or Azure and Git/GitHub.
Practical knowledge of data and risk regulation such as the Australian Privacy Principles (APP), GDPR, along with a practical knowledge of ASIC / APRA standards (e.g. CPS 230, CPG 234/235), and an understanding of SOC 2 and ISO 27001 and frameworks and controls that satisfy them.
Practical knowledge of governance, engineering, analytics/reporting, data science (AI/ML), architecture and automation.
Behavioural Skills
Sets the standard for responsible, well-governed AI/ML use within the data function as it grows.
Comfortable building from a blank page translates business needs into a sequenced plan and starts delivering without waiting for a perfect brief.
Self-directed, identifies what the business needs rather than waiting to be told.
Hands on mindset, happy to write the query and build a pipeline today, and to develop the team that takes that work on tomorrow.
Commercially focused is able to connect data to business outcomes across underwriting, pricing, claims and operations.
Open and direct communicator who gives and seeks honest feedback, and can explain technical trade-offs clearly to non-technical stakeholders.
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