You’ll join a high-performing Data Science team at the centre of a growing AI and machine learning capability within a large, enterprise environment. This is a 12 month contract based in Melbourne, focused on delivering advanced analytics and production grade Machine Learning solutions that drive measurable commercial impact.
As the Senior Data Scientist, you’ll take ownership of designing, building, and deploying scalable machine learning models using Azure Machine Learning. You’ll operate across the full ML lifecycle, from proof of concept through to production, ensuring solutions are robust, reliable, and aligned to business outcomes. Success in this role means delivering models that don’t just work in theory but create real value in-market.
This is: what you’ll do
- Partner with stakeholders to identify high-value AI/ML use cases and define measurable success metrics
- Design, develop, and deploy end to end machine learning solutions using Azure ML
- Lead rapid proof of concept development to validate feasibility and business impact
- Own feature engineering, model selection, hyperparameter tuning, validation, and performance optimisation
- Implement and enhance MLOps practices, including CI/CD, automated monitoring, drift detection, and retraining
- Build and maintain scalable ML pipelines for batch and real time inference via Azure ML Endpoints
- Collaborate with data engineers and software engineers to integrate feature stores and production grade data pipelines
- Lead code reviews and contribute to solution design workshops to uplift technical standards
- Present insights, demos, and recommendations to both technical and non-technical stakeholders
- Mentor and support other data scientists, fostering a strong culture of learning and technical excellence
This is: what you’ll need
- 5+ years’ hands-on experience delivering ML models from development through to production
- Strong expertise in Python and SQL (R or other languages for experimentation advantageous)
- Deep experience with Azure Machine Learning, Pipelines, Data Factory, and MLOps frameworks
- Proven capability across feature engineering, model evaluation, optimisation, and lifecycle management
- Experience implementing CI/CD for ML, automated retraining strategies, and cloud-based ML infrastructure
- Demonstrated success delivering and iterating on proof-of-concepts in fast-paced environments
- Strong stakeholder engagement skills, with the ability to translate complex analytics into business value
- Exposure to recommendation systems, time series forecasting, or geospatial analytics (desirable)
This is: the perks
- Work on large-scale, enterprise AI initiatives with regional impact
- Influence architecture and ML standards across multiple business domains
- Access to cutting-edge tooling and high-performance hardware
This is: for good
Apply with purpose. Be part of a placement that gives back. For every role we fill, we donate to a charity of the client’s choice. We’ve surpassed $1 million donated and we’re just getting started.
This is: what’s next
Apply now or reach out to:
Leanne O’Connor
Director, Natural Selection Group
M: 0402 145 774
E: leanne.oconnor@naturalselectiongroup.com.au