Machine Learning Ops Eng II

AI and Data Science Project Implementation:Leads the development, implementation, and scaling of machine learning models and other AI-driven projects within the Data & Analytics team.Collaborates with data scientists and other stakeholders to translate complex model requirements into operational systems.Ensures robust and scalable infrastructure to support AI deployments and continuous learning cycles. Advanced Data Analysis and Modeling:Utilizes SQL, Python, and dbt to build and optimize data models that support complex queries and analyses essential for AI projects.Interprets data analysis results and communicates findings to both technical and non-technical stakeholders, ensuring actionable insights. Collaboration and Support:Works closely with healthcare professionals, researchers, and administrators to define and refine data requirements for AI applications.Provides expert guidance and mentorship to junior engineers and other team members on data science and engineering best practices. Project Management:Manages multiple AI and data science projects, ensuring effective communication, adherence to timelines, and delivery within budget.Acts as a project lead, coordinating efforts across different teams and ensuring project milestones are met.Develops project plans, tracks progress, and adjusts resources and timelines as needed to ensure successful project delivery. Innovation and Technology Integration:Partner with Innovation and Digital Health Accelerator to operationalize AI within BCH.Actively seeks and integrates new technologies and methodologies to enhance the capabilities of AI projects and data processes.Stays informed of the latest industry trends and technologies, advocating for the adoption of innovative solutions that can provide competitive advantages.Encourages and leads initiatives to explore and adopt innovative solutions that provide competitive advantages. Quality Assurance and Compliance:Ensures the integrity and reliability of data used in AI and machine learning projects, adhering to quality standards and compliance requirements.Maintains comprehensive documentation of all data processes, models, and code to ensure reproducibility and adherence to internal and external regulations.Conducts regular code reviews and quality checks to ensure best practices are followed and standards are met.