Description
Data Linkage Task Lead5377
CALIBRE Systems, Inc. is an employee-owned, mission-focused solutions and digital transformation company. We are looking for a highly motivated Data Linkage Technical Task Lead to join our dynamic team supporting a federal client. This position is involved with the delivery of secure, high‑quality, and scalable linkage, and the preparation, documentation, and distribution of Center for Medicare and Medicaid (CMS) and other data to support comprehensive research analysis through automated, AI-enabled workflows.
Responsibilities include, but are not limited to:
· Lead Data Linkage subtasks, including linkage execution and data preparation.
· Assemble and manage teams performing deterministic, probabilistic, and Privacy Preserving Record Linkage (PPRL) linkages.
· Manage production of study specific linked files and documentation.
· Own functional delivery areas such as:
o Linkage methodology and validation
o Masking and minimum necessary implementation
o Longitudinal file construction
· Ensure technical quality and reproducibility of linkage outputs.
· Communicate linkage status, risks, and results to Project Manager.
· Lead and oversee deterministic, probabilistic, and PPRL based linkages across:
o CMS administrative claims
o Other federal datasets
o National Institute of Health (NIH) funded study data
o Private and non-clinical datasets (e.g., demographic, environmental data)
· Define and govern linkage methodologies, validation protocols, and quality metrics (e.g., precision, recall, reproducibility, error rates).
· Ensure compliance with:
o CMS Data Use Agreements (DUAs)
o NIH data security and privacy policies
o FISMA Moderate and NIST 800 53 requirements
· Oversee production of linkage deliverables, including:
o Study Linkage Reports
o Linkage Production Reports
o Monthly Data Linkage Reports
o Personally identifiable information (PII)/PPRL methodology white papers
· Direct the use of automation and AI enabled methods to improve scalability, validation, and linkage accuracy.
· Ensure adherence to minimum data necessary principles and data masking requirements.
· Coordinate closely with Enclave, Program Operations, and Privacy Preserving Record Linkage Automation tasks.
· Serve as the senior scientific and technical point of contact with NIH, CMS (ResDAC), and other federal stakeholders.
- Deep knowledge of statistical linkage methodologies
- Strong understanding of data management standards and best practices
- Knowledge of federal data security and privacy requirements
- Ability to communicate complex technical and statistical concepts clearly (written and verbal)
Preferred Skills
- SAS Advanced Analytics Certification
- Python or R Data Science Certification
- Familiarity with Master Data Management (MDM) and metadata-driven linkage pipelines
- Familiarity with automated ETL pipelines and AI-enabled data transformation
- Doctoral degree in Health Services Research, Social Sciences, Economics, Behavioral Science, or related discipline
- Experience performing and overseeing large-scale, multi-way data linkages
- Experience working with CMS and federal administrative datasets
- Experience leading work for or with a federal agency
- 25 years of experience serving as a Task Lead on efforts of comparable size and complexity
- 5+ years of technical experience working with large, complex datasets
- Relevant professional certifications (e.g., CAP, CDMP, or similar)
Preferred Experience
- Experience producing publicly released technical white papers or methodological guidance
- Experience with AI-assisted linkage validation and anomaly detection
- Experience integrating linkage outputs into secure research enclaves
- Experience supporting NIH, CMS, or HHS-sponsored data linkage initiatives
- Experience supporting CMS VRDC access or serving as a DUA data custodian
- Experience producing machine-readable documentation and searchable data dictionaries
- Experience supporting research cohorts with longitudinal or administrative claims data
- Experience managing technical assistance programs for research users
Rockville, Maryland, United States
Full-Time/Regular
PI284201032
