Data Innovation Analyst – Laboratory Information Systems (LIS)

Summary / Purpose

The Data Innovation Analyst for LIS will work at the intersection of laboratory operations, IT/informatics and data innovation.

• Focus: Data Innovation
• Contract through July 31, 2026
• Travel: One week per month plus go-live

Areas of Focus:

• enable and drive new data-driven capabilities and workflows within the LIS environment;

• analyze, optimize and enhance the LIS and related data systems to better support lab operations, diagnostics and reporting;

• partner with laboratory staff, IT/BI teams and external vendors to translate data and process insights into innovation and sustained improvements.

Key Responsibilities

• Act as liaison between laboratory operations (clinical labs, instrumentation, specimen workflows) and IT/informatics teams to understand requirements, workflows and data flows.

• Evaluate current LIS environment, data interfaces, data quality, reporting and analytics capabilities; identify gaps, opportunities and “innovation” areas (for example automation of workflows, advanced analytics, dashboarding).

• Design, develop and implement enhancements, new modules, interfaces or integrations in the LIS (or between LIS and other systems) to enable improved efficiency, data capture, instrument connectivity, result reporting, etc. For example: building or improving instrument interfaces, auto-verification rules, data pipelines.

• Perform data analysis: extract, transform and load (ETL) laboratory/test data; generate reports and dashboards; identify trends, anomalies and opportunities for process improvement; support decision-making.

• Lead or support projects: define project scope, schedule, deliverables; collaborate with vendors, lab staff, IT teams; test system changes and ensure validation/verification of enhancements. 

• Ensure system and data integrity, compliance with regulatory and accreditation standards (e.g., College of American Pathologists (CAP) requirements, HIPAA, CLIA if applicable).

• Maintain documentation: system configurations, workflows, user manuals, interface specifications, test scripts.

• Provide training and support to laboratory end-users on new features, data tools and system enhancements.

• Stay current with industry trends (laboratory information systems, data analytics, instrumentation connectivity, health data standards) and propose innovative solutions to enhance operations and data use.