Platform Expert - Energy Sector - #228593

• Proficiency in Azure Machine Learning: The candidate should be proficient with Azure Machine Learning platform, including creating and managing workspaces, experiments, compute resources, and datasets.
• Experience with Azure Databricks: The candidate should have experience with Azure Databricks for big data analytics. This includes knowledge of creating Databricks workspaces, clusters, notebooks, jobs, and tables.
• Knowledge of Machine Learning and Data Science: A strong understanding of machine learning algorithms and data science concepts is necessary. This includes data cleaning, preprocessing, feature engineering, model training, and evaluation.
• Experience with Spark: Experience with Spark for big data processing is important. This includes knowledge of Spark SQL, DataFrames, and MLlib.
• Familiarity with Azure Services: The candidate should be familiar with other Azure services that can be integrated with Azure Machine Learning and Databricks, such as Azure Data Factory, Azure Synapse Analytics, Azure Storage, etc.
• Cloud Computing: Deep understanding of cloud computing concepts, including virtual machines, containers, serverless computing, and cloud storage.

• Experience with Machine Learning Frameworks: Familiarity with frameworks like TensorFlow, PyTorch, Keras, etc., is important.
• Familiarity with MLOps Tools: Experience with tools like Kubeflow, MLflow, TFX, Seldon, etc., that help in the deployment, monitoring, and maintenance of machine learning models.
• Knowledge of DevOps Practices: Understanding of DevOps practices like CI/CD is important.
• Familiarity with GitHub and Azure DevOps would be a plus.
• Soft Skills: Good communication skills to explain complex concepts to non-technical stakeholders, problem-solving skills, and ability to work in a team are also important.

vuUZGU4uwt