Data Scientist
12-month contract
Negotiable on day rate, open to Pty Ltd
Azure Machine Learning (Azure ML) and MLOps best practices.
Key Responsibilities:
Understand business needs & value creation.
Collaborate with stakeholders to identify business challenges where AI/ML can drive measurable improvements.
Define success metrics and ensure alignment with business objectives.
Rapidly build and validate ML prototypes to demonstrate feasibility and value.
Iterate based on feedback, refining models and methodologies for production readiness.
Build and deploy scalable ML solutions
Design, develop, and deployend-to-end AI/ML models onAzure MLto solve complex commercial challenges
Own the entire ML lifecycle, includingdata preprocessing, feature engineering, model selection, hyperparameter tuning, model validation, deployment, and monitoring.
Optimisefeature extraction techniques,



implementrobust model evaluationstrategies, and ensureeffective inference for real-time and batch scoringusingAzure ML Endpoints.
Develop effective and reusable ML workflows and pipelines, ensuringautomated feature engineering, model retraining, and performance trackingacross multiple projects.
Implement and enhance MLOps strategies, integratingCI/CD, automated monitoring, drift detection, and model retraining mechanismsto maintain model integrity over time.
Collaborate with data engineers and software engineersto integratefeature stores, scalable data processing pipelines, and model-serving frameworksinto production applications, ensuring seamless deployment and reliability.
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📌 Data Scientist (Melbourne)
🏢 Mode Talent
📍 Melbourne