Job Overview     

• Develop, test, and maintain Python-based applications, scripts, and tools.
• Develop and implement robust Python-based solutions to efficiently read, process, and transform large datasets from Azure Data Lake Storage (ADLS) Gen2, Synapse and Databricks environments, ensuring data quality and readiness for model development.
• Design, implement, and train machine learning models using relevant Python libraries (e.g., scikit-learn, TensorFlow, PyTorch, MLflow within Databricks) to address specific business problems, iterating on model architecture and hyperparameters to achieve optimal performance.
• Develop and implement automated pipelines and deployment strategies (e.g., using Databricks Model Serving, Azure Machine Learning, containerisation) to seamlessly integrate trained models into production environments, ensuring scalability and reliability.
• Design and build automated workflows using Python and Azure services (e.g., Azure Data Factory, Databricks Workflows) to streamline data ingestion, model training, evaluation, and deployment processes, ensuring efficiency and repeatability.
• Implement monitoring solutions to track model performance and data drift in production, perform regular model evaluation, and develop strategies for model retraining and maintenance to ensure continued accuracy and relevance.
• Effectively collaborate with data engineers, business analysts, and other stakeholders to understand business requirements, communicate technical findings, and contribute to the overall data science strategy.  

• Proficiency in Python and its frameworks (e.g., Django, Flask, FastAPI).
• Solid proficiency in Python programming and relevant data science libraries (e.g., Pandas, NumPy, scikit-learn).
• Demonstrable experience building, training, and evaluating machine learning models using frameworks such as scikit-learn, TensorFlow, PyTorch, or similar.
• Strong problem-solving and analytical skills with the ability to translate business requirements into technical solutions.
• Experience with RESTful APIs and microservices architecture.