Clinical Informatics Specialist

InterSystems•Boston, MA

3d•$120,000 - $143,000•Remote

About The Position

We are seeking a highly skilled Clinical Informatics Specialist to play a pivotal role in the architecture and development of our canonical data model and transformation framework within the InterSystems ecosystem. Focus areas include data modeling, comprehensive documentation, and validating clinical workflows to ensure real-world clinical alignment. In this role, you will act as the bridge between clinical experts and technical engineering teams. You will be responsible for translating clinical needs into product requirements, defining complex data mappings, validating clinical logic, and ensuring our data models adhere to global HIT standards (FHIR, HL7v2, CDA, OMOP, etc.) while maintaining the highest standards of patient safety and data privacy.

Requirements

Clinical degree (MD, DO, RN, PharmD, NP/PA) with active or previous licensure preferred; OR equivalent deep domain experience in Health Informatics.
5+ years of experience in clinical informatics, data modeling, or interoperability analysis.
Proven experience working within InterSystems IRIS for Health or HealthShare environments is highly desired.
Deep mastery of HL7v2, C-CDA, and FHIR (resources, profiles, and implementation guides).
Proficiency with LOINC, SNOMED CT, ICD-10, and RxNorm browsers and hierarchy structures.
Experience with mapping tools, SQL, and data modeling software.
Understanding of ONC certification rules (USCDI), TEFCA, and CMS interoperability rules.
Ability to demystify technical jargon for clinicians and clinical workflows for developers.
Strong capability to visualize data flows and identify edge cases in complex clinical scenarios.
Excellent written and verbal communication skills for creating documentation and specifications.
AI Fluency: Comfort using AI/LLM-based tools (e.g., coding assistants, document drafting copilots, terminology mapping aids) to improve productivity; ability to critically evaluate AI-generated outputs for clinical correctness and safety.

Nice To Haves

Experience with other major integration engines combined with a willingness to learn InterSystems technology will also be considered.
Familiarity with OMOP CDM or openEHR archetypes is a strong plus.

Responsibilities

Manage the governance of the canonical data model definition and maintenance processes in alignment with product strategy, ensuring it supports diverse clinical domains across the care continuum.
Design and document detailed logic for data transformations and mappings between various healthcare data standards (e.g., HL7v2, C-CDA, FHIR, X12, OMOP, openEHR).
Analyze emerging national and international Implementation Guides and regulatory standards, translating them into technical specifications for the engineering team to support future product capabilities.
Serve as the subject matter expert on standard terminologies and code sets, (e.g., SNOMED CT, LOINC, ICD-10, CPT/HCPCS, RxNorm).
Define concept maps and value sets to ensure semantic interoperability across the platform.
Troubleshoot terminology binding issues that arise during data ingestion or exchange.
Collaborate with clinical subject matter experts (SMEs) to gather requirements and translate "clinical intent" into precise technical specifications.
Author functional specifications that allow engineers to build robust interoperability pipelines within InterSystems product suite.
Act as a translator, explaining complex technical data constraints to clinicians and complex clinical workflows to engineers.
Validate data models and transformation logic to ensure they are clinically sound and accurately reflect the patient story.
Conduct clinical safety assessments on proposed data structures to identify and mitigate risks related to data loss, misinterpretation, or context stripping.
Ensure all data designs comply with privacy regulations (HIPAA, GDPR) and data governance policies.
Leverage AI-assisted tools (e.g., large language models, copilots) to accelerate documentation, specification authoring, and data mapping workflows – while applying clinical judgment to validate outputs for accuracy and patient safety.