Data Manager

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 will provide 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 ALLFTD Data Manager will support the collection, organization, quality control, cleaning, integration, and preparation of research data associated with these projects. Responsibilities will include reviewing and reconciling data from multiple internal and external sources; identifying and resolving discrepancies; preparing datasets for research use, reporting, and downstream ingestion; maintaining reproducible data workflows; and supporting data transfers and reporting activities.

They'll work closely with UCSF IT, ALLFTD data teams at partner institutions, data systems personnel, and other technical collaborators to ensure that data are appropriately structured, cleaned, documented, and prepared for transfer into supported research systems.

Department Overview

The UCSF Edward and Pearl Fein Memory and Aging Center (MAC) is an internationally recognized clinical and research center focused on neurodegenerative diseases. With more than 300 employees across the UCSF Mission Bay campus, the MAC provides specialized clinical care and conducts a broad portfolio of observational studies, clinical trials, and translational research. The MAC is home to both a California Alzheimer’s Disease Research Center and a federally funded Alzheimer’s Disease Research Center.

The MAC Genetics and Biospecimen Program supports research across neurodegenerative diseases by facilitating the collection, management, characterization, and responsible use of biospecimens and associated genetic and research data. Through highly characterized participant cohorts and collaborations with investigators within UCSF and at external institutions, the program supports biomarker discovery, genetic research, and the development of improved approaches to understanding, diagnosing, and monitoring disorders, including Alzheimer’s disease and frontotemporal lobar degeneration (FTLD).

DUTIES & ESSENTIAL JOB FUNCTIONS

% 

of time

Essential Function

Key Responsibilities

10

Research Data Systems and Reporting. Maintains and develops research data gathering, retrieval, tracking, and reporting workflows supporting ALLFTD and Boxer Lab research projects.

• Develops and maintains reproducible data extraction and reporting workflows using scripts, queries, and supported research data systems, with Excel used as appropriate for project-specific data review and reporting.
• Supports project-specific operational reporting and, as needed, data reporting associated with biospecimen activities and recharge/billing processes.

10

Cohort Feasibility and Research Support. Provides data feasibility information to support ALLFTD and Boxer Lab study design and research activities.

• Queries available data to assess cohort size, participant characteristics, biospecimen availability, and other relevant research criteria.
• Works with the Genetics and Biospecimen Program Manager, investigators, and research staff to identify appropriate participants, specimens, or datasets for approved research activities.

15

Data Queries, Research Datasets, and Reporting.Prepares queries, datasets, summaries, and reports in support of ALLFTD and Boxer Lab research activities.

• Performs data querying, extraction, organization, and summarization for approved research and operational requests.
• 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.

15

Reproducible Data Workflows and Technical Coordination. Develops and maintains reproducible processes for organizing, cleaning, transforming, and preparing research data.

• Implements and modifies scripts and queries to support recurring data-management and data-return needs.
• Works collaboratively with IT, and other technical personnel to define data requirements and prepare appropriately cleaned and structured datasets for transfer or ingestion into supported systems.
• Troubleshoots data issues in consultation with technical experts as needed. 

30

Data Integration, Quality Control, and Discrepancy Resolution.Aggregates, cleans, integrates, and performs quality control of research data supporting ALLFTD and Boxer Lab projects.

• Regularly receives and integrates datasets from internal and external laboratories, collaborators, and research partners.
• Reviews identifiers, dates, values, specimen information, and other key data elements for completeness, consistency, and accuracy.
• Identifies, investigates, documents, and helps resolve discrepancies in collaboration with laboratory personnel, research staff, investigators, and external partners.
• Prepares validated and appropriately structured data for downstream use, transfer, reporting, or ingestion.

15

Scheduled Data Deliverables and Data Transfers. Coordinates recurring and project-specific data preparation and transfer activities for ALLFTD and Boxer Lab projects.

• Supports timely preparation of datasets for scheduled study deliverables, external collaborators, laboratories, repositories, and internal research systems.
• Performs quality control prior to transfer and maintains appropriate documentation of data versions and deliverables.
• Coordinates with technical and research partners to address data issues identified during transfer or ingestion.

5

Genetics and Biospecimen Program Support. Provides data-management support for broader Genetics and Biospecimen Program, laboratory, or MAC research needs when appropriate and as assigned by the Genetics and Biospecimen Program Manager.

• May assist with time-limited data cleaning, reporting, troubleshooting, or other data-management activities supporting shared programmatic needs.
• Such activities are secondary to the position's primary responsibilities supporting ALLFTD and Boxer Lab research projects.

100%

Required Qualifications

• Bachelor's degree in related area and minimum one year of experience or equivalent experience / training.
• Working knowledge of research function.
• 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 MS Office skills.
• Proficiency in a programming language (python, R, etc.).
• Experience with source control management (e.g. git) and best practices for scripting.
• Working skills in analysis and consultation.
• Ability to communicate complex information clearly and concisely, both verbally and in writing, and to work collaboratively with research and technical colleagues.
• Ability to multitask and be organized and work quickly in a dynamic environment with competing priorities.

Preferred Qualifications

• Minimum of 3 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.