Data Science & Analytics Lead

Data Science & Analytics Lead

ASRT is seeking a Data Science & Analytics Lead to provide senior technical leadership for The Center for Disease Control and Prevention (CDC) healthcare-data modernization, advanced analytics, clinical-data interoperability, enterprise data architecture, and data-science strategy. This individual will advise CDC leadership and scientific teams on how to integrate large healthcare datasets, interoperability standards, common data models, cloud technologies, metadata, governance, and advanced analytics into scalable and secure public-health surveillance solutions.

This position represents one of the most specialized roles in Task Area 2 and requires a combination of healthcare informatics, data science, interoperability, analytics, and enterprise technology experience.

-DSAL

Atlanta, GA, USA

As required to fulfill the responsibilities of the position

• Lead assessment of CDC data, analytical, and information-system requirements.
• Recommend modern analytical and computational architectures.
• Provide senior guidance on data science, analytics, machine learning, visualization, cloud, and CDC-approved AI approaches.
• Support integration and modernization of data systems and enterprise services.
• Advise on scientific-data curation, metadata, provenance, lineage, governance, and stewardship.
• Design strategies for management and analysis of large healthcare datasets.
• Advise on cloud-based and distributed analytical environments.
• Support development and implementation of enterprise data and metadata standards.
• Provide technical leadership concerning clinical-data interoperability and common data models.
• Guide development, validation, and management of electronic phenotypes and clinical case definitions.
• Support the use of EHR, claims, clinical, pharmaceutical, and commercial healthcare datasets for public-health surveillance.
• Collaborate with CDC technical governance, leadership, epidemiologists, statisticians, and scientific stakeholders.
• Develop roadmaps for enterprise data, analytics, and knowledge-management systems.
• Evaluate technical problems and recommend corrective actions.
• Ensure technical solutions align with CDC enterprise platforms, governance, architecture, and security requirements.
• Support migration from siloed analytical environments into enterprise capabilities where appropriate.

• Master’s degree in Health Informatics, Data Science, Epidemiology, Statistics, Economics, or related discipline, consistent with CDC’s Task 14 requirement.

• PhD or doctoral work in Health Informatics, Data Science, Epidemiology, Statistics, or Economics.

• 8 years of progressively responsible data science, Health Informatics, analytics, healthcare-data, or information-systems experience.
• Significant experience using R, Python, and SQL.
• Experience managing and analyzing large healthcare datasets.
• Demonstrated knowledge of healthcare interoperability standards, including HL7 and FHIR.
• Experience with healthcare common data models.
• Experience with Power BI or comparable visualization platforms.
• Experience with cloud-based analytics.
• Experience translating technical/data-science requirements into recommendations for scientific or executive stakeholders.

• OMOP/OHDSI expertise.
• Health Verity, Premier, Truveta, IQVIA, PCORnet, Market Scan, or comparable commercial/aggregated healthcare datasets.
• CMS, HRSA, VA, DHA, or other Federal healthcare datasets.
• Electronic phenotypes and clinical case definitions.
• Distributed computing and large relational databases.
• Microsoft Azure.
• CDC EDAV/1
  
  CDP.
• CDC Data Modernization Initiative experience.
• Clinical quality measures and public-health surveillance using EHR/claims data.
• Federal healthcare data modernization.

• Candidates should possess at least five years of relevant data analysis experience, consistent with the approved GSA labor category, with senior level candidates expected to demonstrate substantially greater depth. Experience should include complex data analysis, data quality management, reporting, dashboards or…