Remote Clinical Informatics Specialist — Workflows & Data

Alignerr Corp.; Seattle (WA); Remote; USD 55,000 - 165,000; Part time

Benefits offered by this job

Fully remote

Flexible schedule

Contract extensions possible

Freelance autonomy

Job summary

Alignerr Corp. is seeking a Clinical Informatics Specialist to evaluate EMR-driven workflows, assess decision-support logic, and identify critical gaps in how clinical data is structured, shared, and used across health IT.

This fully remote hourly contract role expects you to review data schemas, surface inconsistencies, interpret standards (FHIR, HL7, SNOMED), and document edge cases with precision, supporting ongoing data quality and interoperability initiatives.

Qualifications

• Experience in clinical informatics, healthcare IT, or clinical operations.
• Strong knowledge of EMR systems and clinical data standards.
• Ability to interpret standards like FHIR, HL7, SNOMED.
• Detail-oriented and able to work independently.
• Excellent data quality assessment and documentation skills.

Responsibilities

• Review EMR-driven workflows and data structures to identify inefficiencies and gaps.
• Evaluate decision-support logic and surface inconsistencies or opportunities for improvement.
• Summarize workflow behavior and document edge cases with precision.
• Assess data quality, interoperability, and transformation logic across healthcare systems.
• Interpret clinical standards, terminologies, and mapping frameworks (FHIR, HL7, SNOMED).
• Support recurring reviews of healthcare-informatics datasets to ensure ongoing accuracy and alignment.

Skills

Clinical informatics

EMR systems

Data schemas

FHIR/HL7/SNOMED

Analytical thinking

Clear communication

Independent work

Job description

Alignerr Corp. is seeking a Clinical Informatics Specialist to evaluate EMR-driven workflows, assess decision-support logic, and identify critical gaps in how clinical data is structured, shared, and used across health IT.

This fully remote hourly contract role expects you to review data schemas, surface inconsistencies, interpret standards (FHIR, HL7, SNOMED), and document edge cases with precision, supporting ongoing data quality and interoperability initiatives.