Data Manager

UCSF•San Francisco, CA

7d•$36 - $78

About The Position

The Data Manager position is based within the UCSF Edward and Pearl Fein Memory and Aging Center (MAC), a multidisciplinary clinical research program investigating neurodegenerative diseases. Under the direct supervision of the Genetics and Biospecimen Program Manager, the ALLFTD Data Manager provides data management support for ALLFTD, a multisite longitudinal study of frontotemporal lobar degeneration, and selected Boxer Lab projects focused on biomarker discovery in neurodegenerative diseases. The role supports the collection, organization, quality control, cleaning, integration, and preparation of project research data. It includes reviewing and reconciling data from internal and external sources; identifying and resolving discrepancies; preparing datasets for research use, reporting, and downstream ingestion; maintaining reproducible workflows; and supporting data transfers and reporting. The Data Manager works closely with UCSF IT, data teams at ALLFTD partner institutions, data systems personnel, and other technical collaborators to ensure data are appropriately structured, cleaned, documented, and ready for transfer into supported research systems. The MAC is an internationally recognized clinical and research center focused on neurodegenerative diseases, with more than 300 employees across UCSF’s Mission Bay campus. It provides specialized clinical care and conducts observational studies, clinical trials, and translational research. Its Genetics and Biospecimen Program supports research through biospecimen and associated genetic and research data management, working with characterized participant cohorts and collaborators within UCSF and at external institutions.

Requirements

Bachelor’s degree in a related area and a minimum of one year of experience, or equivalent experience or training.
Working knowledge of research function.
Working skills in systems programming, scripting, and statistical software packages.
Proven track record of successfully managing and maintaining accurate data in a complex data environment.
Demonstrated proficiency in statistical analysis, data transformation and linking, data systems programming, and/or data schema design and documentation.
Prior experience working in a research environment, preferably in or closely with a wet lab.
Excellent Excel and Microsoft Office skills.
Proficiency in a programming language such as Python or R.
Experience with source control management (e.g., Git) and scripting best practices.
Working skills in analysis and consultation.
Ability to communicate complex information clearly and concisely, verbally and in writing, and collaborate with research and technical colleagues.
Ability to multitask, stay organized, and work quickly in a dynamic environment with competing priorities.

Nice To Haves

At least three years of research or clinical data management experience.
Basic understanding of genetics and proteomics.
Experience working with relational databases or software tools to design queries and reports.
Knowledge of HIPAA and best practices for securing protected health information.

Responsibilities

Maintain and develop research data gathering, retrieval, tracking, and reporting workflows for ALLFTD and Boxer Lab research projects.
Develop and maintain reproducible data extraction and reporting workflows using scripts, queries, and supported research data systems; use Excel as appropriate for project-specific review and reporting.
Support operational reporting and, as needed, reporting related to biospecimen activities and recharge or billing processes.
Query available data to assess cohort size, participant characteristics, biospecimen availability, and other research criteria.
Work with the Genetics and Biospecimen Program Manager, investigators, and research staff to identify appropriate participants, specimens, or datasets for approved research activities.
Prepare queries, datasets, summaries, and reports for research and operational requests.
Extract, organize, and summarize data for approved requests; prepare clean, appropriately structured datasets for investigators, collaborators, and other authorized recipients.
Document data sources, transformations, and relevant limitations to support accurate interpretation and reproducibility.
Implement and modify scripts and queries for recurring data-management and data-return needs.
Coordinate with IT and other technical personnel to define data requirements and prepare cleaned, structured datasets for transfer or ingestion into supported systems; troubleshoot data issues with technical experts as needed.
Regularly receive and integrate datasets from internal and external laboratories, collaborators, and research partners.
Review identifiers, dates, values, specimen information, and other key data elements for completeness, consistency, and accuracy.
Identify, investigate, document, and help resolve discrepancies with laboratory personnel, research staff, investigators, and external partners.
Prepare validated and appropriately structured data for downstream use, transfer, reporting, or ingestion.
Prepare datasets for scheduled study deliverables, external collaborators, laboratories, repositories, and internal research systems; perform quality control and document data versions and deliverables.
Coordinate with technical and research partners to address issues identified during transfer or ingestion.
Provide additional data-management support for broader Genetics and Biospecimen Program, laboratory, or MAC research needs as assigned; this may include time-limited data cleaning, reporting, troubleshooting, or other programmatic activities.