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·Analysis and Development
Lead the development and implementation of ML standards, processes and best practices. Collaborate with stakeholders to identify and plan for enterprise ML portfolio needs. Oversee ML team members on their deliverables and activities. Set and continuously refine ML development standards to ensure scalability and accuracy to meet the enterprise needs. Work closely with data scientists and data engineers to oversee development of machine learning models. Evaluate metrics to continuously evaluate the performance of machine learning solutions. Extend and democratize machine learning practice across business units.

·Technical and Business Skills
Mastery in machine learning models for classifications, decision trees, support vector machines and deep learning. Strong understanding of probability and statistical mduckodels (generative and descriptive models). Advanced programming skills with Python C/C++, R, Java. Experience with numerical and data science libraries (scikit-learn, Pandas, NumPy, kernlab, etc.). Experience with at least one major machine learning framework (TensorFlow, PyTorch, etc.). Experience in DevOps/MLOps. Understanding of data structures, data modeling and software architecture. Advanced background of probability, statistics, and algorithms. Deep understanding of core CCHMC/healthcare clinical, business and research processes to help build appropriate data solutions. Build additional skills and understand cutting edge data engineering advances through continuing education. Lead experimentation to analyze results using machine learning models. Effectively communicate technical concepts and results to technical and business audiences in a comprehensive manner. Strong background with collaboration across multiple teams and stakeholders, including analytics teams, development teams, product management and operations. Stay abreast of trends in AI/ML and identify action plan for CCHMC.

·Project Execution & Management
Execute own project tasks with urgency and to a high level of quality. Communicate status clearly and effectively using departmental project management tools. Follow time-tracking and other project management requirements. Participate actively in project meetings, stand-ups, etc. Serve as technical lead for moderately complex projects, collaborating with project managers to ensure project scope/risk/budget/etc. are adequately managed. Lead project meetings and workgroups.