Senior Director, Informatics

Overview

The Senior Director, Informatics leads a team of clinical informatics professionals within the Enterprise Data Strategy organization, serving as both a people leader and subject matter authority in clinical data quality and normalization. This role is responsible for guiding the team's day-to-day work while personally contributing deep expertise in clinical coding, ontology mapping, and data quality analysis to support Inovalon's data normalization strategy and ensure enterprise data products meet rigorous clinical and technical standards. Working in close partnership with Product, Clinical, and Engineering teams, this leader bridges the gap between raw healthcare data and actionable clinical intelligence while developing a team equipped to do the same.

Duties and Responsibilities

• Team Leadership & Development: Lead, mentor, and develop a team of informatics professionals; establish clear objectives, foster a high-performance culture, and support individual growth and career development within the team.
• Subject Matter Leadership: Serve as the team's authority on clinical ontologies and data normalization, providing technical direction and guidance to ensure consistency and quality across all informatics workstreams.
• Clinical Ontology Maintenance: Support and maintain internal reference data processes aligned with industry-standard clinical ontologies, including ICD-10, SNOMED CT, LOINC, and RxNorm, ensuring accuracy and currency of code mappings.
• Data Quality Analysis: Execute data quality monitoring routines to identify, document, and remediate gaps or inconsistencies in healthcare data assets; escalate systemic issues as appropriate.
• Clinical Normalization: Apply and refine clinical normalization techniques to map unstructured and semi-structured clinical information to standardized codified data elements.
• Data Asset Assessment: Support the evaluation of new data assets for depth, specificity, and quality; support Expert Determination workflow; prepare structured assessments and summaries for leadership review.
• Cross-Functional Collaboration: Collaborate closely with Data Engineering, Product, and Clinical teams to ensure that data specifications are accurately implemented and downstream data products reflect high-fidelity source data.
• KPI Reporting & Tracking: Contribute to the development and tracking of Data Quality (DQ) KPIs and benchmarks; generate periodic reporting.