Roles and Responsibilities

• Lead and manage the design, development, and deployment of advanced machine learning models, ensuring alignment with business goals and technical requirements.
• Drive innovation in machine learning, leveraging both supervised and unsupervised learning techniques, along with deep learning frameworks such as Scikit-learn, TensorFlow, Keras, and PyTorch.
• Spearhead personalization initiatives in the e-commerce domain, developing solutions that optimize customer experiences and engagement.
• Collaborate with cross-functional teams to integrate machine learning models and data pipelines into production systems, ensuring scalability and performance.
• Oversee the implementation of MLOps practices in cloud environments, particularly using Azure and Databricks, to streamline model deployment, monitoring, and maintenance.
• Provide technical leadership in cloud technologies, with extensive hands-on experience in Microsoft Azure Cloud and Databricks.
• Champion best practices in DevOps/MLOps, enhancing the efficiency and reliability of data science operations.
• Communicate complex technical concepts to both technical and non-technical stakeholders, ensuring clear and effective decision-making.

Required Skills and Experience

• 12-15 years of experience in data engineering, machine learning engineering, or data science.
• Expertise in Python, PySpark, and a strong foundation in machine learning (supervised and unsupervised) and deep learning frameworks.
• Proven experience leading personalization projects in the e-commerce space, with a focus on improving customer-centric outcomes.
• Hands-on experience with MLOps frameworks, particularly in Azure and Databricks, with a strong emphasis on automation and model lifecycle management.
• In-depth knowledge of Microsoft Azure Cloud services and Databricks for end-to-end data engineering and machine learning workflows.
• Familiarity with DevOps/MLOps practices and tools, ensuring robust model deployment and monitoring pipelines.
• Strong verbal and written communication skills, with the ability to effectively present technical concepts to a wide range of stakeholders.
• Bachelor’s degree in Computer Science, Statistics, Engineering, or a related field. Advanced degrees are a plus.

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