Data Scientist Azure ML
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.
Develop quick proof-of-concepts
- 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 deploy end-to-end AI/ML models on Azure ML to solve complex commercial challenges
- Own the entire ML lifecycle, including data preprocessing, feature engineering, model selection, hyperparameter tuning, model validation, deployment, and monitoring.
- Optimise feature extraction techniques, implement robust model evaluation strategies, and ensure effective inference for real-time and batch scoring using Azure ML Endpoints.
- Develop efficient and reusable ML workflows and pipelines, ensuring automated feature engineering, model retraining, and performance tracking across multiple projects.
- Implement and enhance MLOps strategies, integrating CI/CD, automated monitoring, drift detection, and model retraining mechanisms to maintain model integrity over time.
- Collaborate with data engineers and software engineers to integrate feature stores, scalable data processing pipelines, and model-serving frameworks into production applications, ensuring seamless deployment and reliability.
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