Analytics Engineer — Data Pipelines & ML Ops for Health
Bupa Australia
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Job summary
Bupa Analytics Engineer is responsible for delivering and productionising Data Science and Analytics projects that improve health insurance outcomes. You will migrate to a new Azure-based data platform, implement an MLOps framework for propensity models, and support insights development with scalable data assets.
Work with stakeholders to translate requirements into data-driven approaches, and collaborate with data program and technology teams to ensure robust pipelines and reusable data
Qualifications
- 3+ years of business experience in customer analytics / data science / data engineering or similar field.
- Engineering using cloud first approaches.
- Data processing frameworks and modern data management practices.
- Agile working rhythms and automation focus.
- Qualified in a quantitative discipline (Statistics, Engineering, CS, ML or related).
- Strong SQL skills; Python preferred; Azure data services exposure.
Responsibilities
- Understand data requirements with stakeholders and translate into data-driven solutions.
- Engineer data pipelines from ingestion to consumption (reports, dashboards, models, APIs).
- Develop reusable data features and drive feature store adoption.
- Monitor data quality and support analytics and ML initiatives within the team.
- Follow Bupa designs, standards, and patterns in deliverables.
Skills
Education
Tools
Job description
Bupa Analytics Engineer is responsible for delivering and productionising Data Science and Analytics projects that improve health insurance outcomes. You will migrate to a new Azure-based data platform, implement an MLOps framework for propensity models, and support insights development with scalable data assets.
Work with stakeholders to translate requirements into data-driven approaches, and collaborate with data program and technology teams to ensure robust pipelines and reusable data
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