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

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