Job Description

Data/AI - Operations Manager Qualifications: 7 to 11 years of experience in operations management, with a focus on data platforms, AI/ML operations, and API support. Strong understanding of AI technologies, machine learning, deep learning, and natural language processing. Hands-on experience with cloud platforms such as AWS and Azure, and data warehousing solutions like Snowflake. Proficiency in programming languages such as Python, R, or Java, and experience with AI frameworks/libraries such as TensorFlow, Py Torch, or scikit-learn. Knowledge of healthcare industry regulations and compliance requirements. Strong analytical, problem-solving, and decision-making skills. Strong communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams. Experience in project management and agile methodologies is a plus. Key Responsibilities: Data Platform Management: Manage the collection, storage, and processing of large datasets required for various business operations. Ensure the reliability, efficiency, and security of data platforms. AI ML Operations Support: Collaborate with data scientists and machine learning engineers to develop, test, and optimize AI and ML models for various use cases. Implement monitoring tools and processes to evaluate the performance of AI/ML systems continuously. Optimize AI/ML algorithms and workflows to enhance accuracy, efficiency, and speed. API Support: Oversee the development and maintenance of APIs to ensure seamless integration between systems and applications. Ensure APIs are reliable, secure, and scalable to meet business needs. Solution Design and Deployment: Support the design, development, and deployment of technology solutions to address business challenges. Work on projects involving predictive analytics, machine learning models, and other advanced technologies. Ensure collaboration on solutions to ensure they are integrated into existing workflows and business processes. Operational Management: Manage Service Level Agreements (SLAs) to ensure high standards of service delivery. Plan and manage shifts for team members to ensure 24/7 operational support. Monitor operational performance and implement improvements as necessary. Ensure all operational processes are well-documented and adhered to. Team Management: Lead a team of engineers and support staff, providing guidance, mentorship, and support to achieve organizational objectives. Foster a collaborative and innovative team environment. Quality Assurance Support: Establish, develop, and implement quality assurance strategies. Oversee testing processes, analyze data, collaborate with cross-functional teams, and drive continuous improvement initiatives. Ensure compliance with industry regulations and internal quality policies.