Job Opportunities API

Why join us? We're a global tech company, just not the kind you're picturing. Our almost 1,000-person team builds tools that make work better for the three billion frontline workers who keep the world moving. We've got big tech scale, without the sign-off layers or corporate theatre. Every permanent team member gets equity, so when we grow, you do too. This next chapter is about scaling smart, powered by AI, a clear vision and real ownership. Big tech impact, without the big tech ick. THE ROLE To support the build out of the end-to-end data, analytics and data science capability for SafetyCulture Care, our insurance business. It turns raw data into the pipelines, models and insight that power underwriting, pricing, risk and operational decisions, starting hands-on as the foundations are laid. KEY RESPONSIBILITIES - Support the delivery of the end-to-end data lifecycle - capture, storage, transformation, modelling, materialisation and insight. Establishing the foundations the insurance business runs on. - Be hands-on in the delivery of data assets and products across data capture, pipelines, reporting and analytical/statistical models. Collaborating with business and technical subject matter experts to deliver best in class assets and products. - Support the selection of, and development of a fit for purpose data architecture and tooling (cloud platform, warehouse, orchestration and business intelligence). - Support the delivery of a fit for purpose data governance and controls framework aligned to applicable regulation so data is trusted, compliant and audit-ready. - Translate underwriting, pricing, claims and operational questions into analysis and models that measurably improve decisions across the business. - Collaborate with business subject matter experts to build out the reporting, semantic layer and self-serve insight layer so leaders and operators across SafetyCulture Care can answer their own questions. - Embed artificial intelligence and machine learning (AI/ML) into core insurance workflows in partnership with actuarial, underwriting, product and engineering. - Support the growth of a geographically and diverse skilled data team across governance, engineering, analytics, data science and automation. REQUIRED SKILLS & EXPERIENCE 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. - Comfortabl