Senior Data Scientist
On-siteSydney, New South Wales, Australia
Job Summary
Lead forecasting and optimisation use cases for parking, aeronautical, retail, and airport operations, partnering with business owners to frame problems and translate model outputs into pricing, capacity, and staffing decisions. Design, build, validate, and productionise models in Python on Azure Machine Learning integrated with Snowflake, while owning the full lifecycle from feature engineering to production monitoring for data drift. Present forecasts and scenario analyses to senior stakeholders to support high-stakes decisions on capacity and revenue strategy. Mentor onshore and offshore data scientists to set technical direction and lift delivery standards.
Required Qualifications
- 7+ years' applied data science, with a track record of models deployed to production and adopted by the business
- Expert in Python (pandas, scikit-learn and related ML/stats libraries) and SQL
- strong foundation in timeseries forecasting, regression, classification and clustering
- Hands-on experience with an enterprise ML platform (Azure ML or equivalent AutoML) and a cloud data warehouse (Snowflake or equivalent)
- Proven MLOps discipline — model deployment, batch-prediction pipelines, monitoring, drift detection and retraining
- Working experience on Microsoft Azure (e.g. Azure ML, Azure DevOps, storage and compute services)
- Excellent stakeholder engagement and data storytelling — able to turn technical results into commercial decisions and present with confidence to executives
- Degree in a quantitative discipline (Statistics, Mathematics, Computer Science, Engineering or Data Science) or equivalent experience
Desired Qualifications
- Aviation, transport, or pricing / revenue-management and forecasting-heavy operational domains
- Power BI, explainable AI, optimisation, and A/B testing frameworks
- Familiarity with Responsible AI governance and privacy-aware analytics
- Experience leading or mentoring distributed onshore/offshore teams
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