Data Manager

University of California, San Francisco•San Francisco, CA

About The Position

The Data Manager 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 role 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 Data Manager supports the collection, organization, quality control, cleaning, integration, and preparation of research data. The role reviews and reconciles data from internal and external sources, investigates and helps resolve discrepancies, prepares datasets for research use, reporting, and downstream ingestion, maintains reproducible data workflows, and supports data transfers and reporting. The position collaborates with UCSF IT, partner-institution ALLFTD data teams, data-systems personnel, investigators, research staff, and other technical collaborators to ensure data are appropriately structured, cleaned, documented, and prepared 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 the UCSF Mission Bay campus. It provides specialized clinical care and conducts observational studies, clinical trials, and translational research. The Genetics and Biospecimen Program facilitates the collection, management, characterization, and responsible use of biospecimens and associated genetic and research data, supporting biomarker discovery and genetic research through characterized participant cohorts and collaborations 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 functions.
Working skills in systems programming, scripting, and statistical software packages.
Proven track record of success 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 a wet lab 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 such as Git and best practices for scripting.
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

Minimum of 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

Maintains and develops research data gathering, retrieval, tracking, and reporting workflows supporting ALLFTD and Boxer Lab projects.
Develops and maintains reproducible data extraction and reporting workflows using scripts, queries, and supported research data systems; uses Excel as appropriate for project-specific review and reporting.
Supports project-specific operational reporting and, as needed, reporting associated with biospecimen activities and recharge/billing processes.
Queries available data to assess cohort size, participant characteristics, biospecimen availability, and other research criteria for study design and research activities.
Works with the Genetics and Biospecimen Program Manager, investigators, and research staff to identify appropriate participants, specimens, or datasets for approved research activities.
Prepares queries, datasets, summaries, and reports for approved research and operational requests.
Queries, extracts, organizes, and summarizes data, and prepares clean, appropriately structured datasets for investigators, collaborators, and other authorized recipients.
Documents data sources, transformations, and relevant limitations to support accurate interpretation and reproducibility.
Develops and maintains reproducible processes for organizing, cleaning, transforming, and preparing research data.
Implements and modifies scripts and queries for recurring data-management and data-return needs.
Works with IT and other technical personnel to define data requirements, prepare datasets for transfer or ingestion into supported systems, and troubleshoot data issues as needed.
Aggregates, cleans, integrates, and performs quality control of research data supporting ALLFTD and Boxer Lab projects.
Reviews identifiers, dates, values, specimen information, and other key data elements for completeness, consistency, and accuracy.
Identifies, investigates, documents, and helps resolve discrepancies with laboratory personnel, research staff, investigators, and external partners.
Prepares validated, appropriately structured data for downstream use, transfer, reporting, or ingestion.
Coordinates recurring and project-specific data preparation and transfer activities, including scheduled study deliverables for collaborators, laboratories, repositories, and internal research systems.
Performs quality control before transfers, documents data versions and deliverables, and coordinates with technical and research partners to address issues identified during transfer or ingestion.
Provides data-management support for broader Genetics and Biospecimen Program, laboratory, or MAC research needs as appropriate and assigned; may assist with time-limited data cleaning, reporting, troubleshooting, or other shared programmatic needs.