Senior Systems Analyst - Machine Learning Engineer (NGEMR)

• Meeting with clinicians, business stakeholders, Epic application analysts, data scientists, and subject matter experts to understand AI and predictive analytics requirements
• Evaluating whether proposed use cases are suitable for machine learning, generative AI, rules-based logic, or existing Epic functionality
• Translating clinical and operational requirements into technical model-integration specifications
• Preparing, validating, and transforming Epic clinical and operational data for model development and inference
• Deploying internally developed or third-party predictive models through Epic Nebula and the Epic Cognitive Computing framework
• Developing and maintaining model input mappings, output mappings, configuration, APIs, and workflow integration components
• Integrating model predictions, risk scores, classifications, recommendations, or generated content into appropriate Epic workflows
• Working with Epic application teams to configure user-facing components such as alerts, decision-support activities, work queues, patient lists, dashboards, or other workflow touchpoints
• Collaborating with data scientists to package models and ensure that model artifacts meet Epic deployment requirements
• Validating model compatibility, dependencies, input schemas, output schemas, and runtime requirements
• Performing unit testing, integration testing, workflow testing, performance testing, regression testing, and user acceptance testing
• Assessing model accuracy, calibration, sensitivity, specificity, false-positive rates, false-negative rates, fairness, and operational impact
• Establishing monitoring for model availability, latency, data quality, prediction distribution, model drift, and workflow adoption
• Investigating production issues involving model execution, data availability, interfaces, workflow configuration, or prediction delivery
• Maintaining model versioning, deployment records, technical documentation, validation evidence, and change-control documentation
• Supporting model promotion across development, test, validation, and production environments
• Participating in Epic upgrades and reviewing changes that may affect Nebula, cognitive computing, data structures, interfaces, or embedded AI workflows
• Ensuring compliance with organizational policies relating to cybersecurity, patient privacy, clinical safety, responsible AI, and data governance
• Supporting periodic model review, recalibration, retraining, rollback, retirement, and replacement
• Providing technical guidance and knowledge transfer to Epic analysts, data scientists, application support teams, and operational users

The position shall also be responsible for:

• External models integrated with Epic
• Real-time and batch inference workflows
• Generative AI and large language model integrations
• Epic Cognitive Computing configuration
• Epic Nebula model deployment and administration
• Model monitoring dashboards
• Feature engineering and reusable feature pipelines
• Integration with Clarity, Caboodle, Chronicles, Cosmos, FHIR, or other approved clinical data sources
• Integration with cloud-based AI or machine learning services
• Clinical decision-support configuration
• AI governance and model inventory management
• Evaluation of third-party healthcare AI products