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