Sr Associate Data Scientist, IT Analytics-24019

Role Overview: You will be part of the Machine Learning domain, focusing on the application of algorithms and models to enable computers to learn from data and make predictions. Your scope will include various subfields such as segmentation, natural language processing, and reinforcement learning. Your role will involve collaborating with leaders, engineers, and product teams to build and deploy machine learning models, troubleshoot and debug complex issues, and research and implement new AI technologies to enhance processes and performance. Key Responsibilities: - Collaborate with various stakeholders to understand requirements and develop AI solutions according to business needs - Maintain and enhance existing enterprise services and applications using domain driven design and test-driven development - Troubleshoot and debug complex issues, identifying and implementing solutions - Create detailed project specifications, requirements, and estimates - Research and implement new AI technologies to improve processes, security, and performance - Build and deploy machine learning models, focusing on technical aspects of model deployment - Implement and optimize Python-based ML pipelines for data preprocessing, model training, and deployment - Monitor model performance, implement bias mitigation and explainability strategies, and ensure scalability and efficiency in production environments - Write and maintain code for model training and deployment, collaborating with software engineers for integration - Work with a diverse team of experts to leverage cutting-edge technologies for scalable AI solutions Qualifications Required: - Bachelor's degree in computer science, Computer Engineering, Data Science, Information Systems, Engineering, or related technical discipline, or equivalent experience/training - 3+ years of full Software Development Life Cycle (SDLC) experience in designing, developing, and implementing large-scale machine learning applications in hosted production environments - Proficiency in Python, Databricks, Azure AI Foundry services, database frameworks, cloud-based development, web servers, web services, AI/ML frameworks, MLOps tools, build/deployment tools, and other Dev Ops Toolchain - Strong understanding of object-oriented design principles, governance frameworks for responsible AI, post-deployment model maintenance, NLP concepts, and Agile methodologies - Experience in developing and implementing generative-based AI solutions, prompt engineering, and proficiency in Microsoft Office Tools - Strong communication skills to effectively interact with stakeholders at all levels, influence through collaboration and negotiation, and work well within a team environment (Note: Physical abilities necessary to perform essential job functions will be assessed as per company policy) Role Overview: You will be part of the Machine Learning domain, focusing on the application of algorithms and models to enable computers to learn from data and make predictions. Your scope will include various subfields such as segmentation, natural language processing, and reinforcement learning. Your role will involve collaborating with leaders, engineers, and product teams to build and deploy machine learning models, troubleshoot and debug complex issues, and research and implement new AI technologies to enhance processes and performance. Key Responsibilities: - Collaborate with various stakeholders to understand requirements and develop AI solutions according to business needs - Maintain and enhance existing enterprise services and applications using domain driven design and test-driven development - Troubleshoot and debug complex issues, identifying and implementing solutions - Create detailed project specifications, requirements, and estimates - Research and implement new AI technologies to improve processes, security, and performance - Build and deploy machine learning models, focusing on technical aspects of model deployment - Implement and optimize Python-based ML pipelines for data preprocessing, model training, and deployment - Monitor model performance, implement bias mitigation and explainability strategies, and ensure scalability and efficiency in production environments - Write and maintain code for model training and deployment, collaborating with software engineers for integration - Work with a diverse team of experts to leverage cutting-edge technologies for scalable AI solutions Qualifications Required: - Bachelor's degree in computer science, Computer Engineering, Data Science, Information Systems, Engineering, or related technical discipline, or equivalent experience/training - 3+ years of full Software Development Life Cycle (SDLC) experience in designing, developing, and implementing large-scale machine learning applications in hosted production environments - Proficiency in Python, Databricks, Azure AI Foundry services, database frameworks, cloud-based development, web servers, web services, AI/ML