Strengthen data quality by reviewing and validating phenotype, sample, and metadata files for clarity and consistency, carefully documenting curation decisions throughout the process.
Standardize phenotype and variable metadata using controlled vocabularies to improve usability across studies.
Identify missing, unclear, or inconsistent documentation and work with study teams to resolve gaps.
Prepare and organize key dbGaP submission components, ensuring alignment with NIH data-sharing and consent requirements.
Implement quality control checks that enhance the accuracy, completeness, and reliability of study submissions.
Support updates to existing dbGaP records, maintaining accurate, current, and well‑documented study metadata.
Collaborate with investigators, researchers, and NCI staff to support timely, transparent, and policy‑aligned data sharing.
What You’ll Need to Succeed
Master’s degree in a relevant scientific or data‑focused discipline (e.g., genomics, biomedical science, bioinformatics) with 1–3 years of submitting dbGaP data, and 4 years curating biomedical data.
Proven experience reviewing, curating, and organizing scientific data, including genomic, phenotypic, and clinical metadata, in fast‑paced or complex research environments.
Strong ability to quickly learn new workflows, study processes, and submission requirements, adapting effectively within an established team structure.
Demonstrated expertise in metadata standards, data dictionaries, variable harmonization, and controlled vocabularies to ensure accuracy and consistency across studies.
Demonstrated technical proficiency with large datasets, including advanced Excel, SQL, Linux/Unix, Python, and R.
Experience performing rigorous quality control checks and identifying documentation gaps or inconsistencies in study materials.
Strong communication skills to coordinate with investigators, NCI staff, study teams, and other stakeholders to resolve questions and obtain missing information.
Ability to interpret consent, data‑use limitations, and NIH data‑sharing policies to ensure compliant and accurate dbGaP submission materials.
Preferred
Background creating large genomic, phenotypic, or epidemiologic datasets in a research environment.
