Biospecimens and Genetics Data Manager

The Biospecimens and Genetics Data Manage gathers, analyzes, and curates a wide variety of research data, primarily involving human biofluids and genetics but also other clinical data elements. Participates in research by supporting data QC, ingesting data from external collaborators, creating datasets to share with researchers, summarizing collected data according, developing data best practices, and faciliating data related activities (e.g., biospecimens’ inventory, billing). Prepares reports, charts, tables, and other visual aids to interpret and communicate data.

The position is with the UCSF Edward and Pearl Fein Memory and Aging Center (MAC) (http://memory.ucsf.edu), a dynamic multidisciplinary clinical research program investigating neurodegenerative diseases. Reporting to the Director of Research Technology, the Specimen Data Manager is responsible for data management activities supporting the Biospecimen Program and its operational work.

They manage data workflows supporting several large studies that collect human fluid (e.g., blood, spinal fluid) specimens. Responsibilities include fluid derived data management, including QC, data wrangling, generation of metrics, and reporting for data ingestion and dataset generation. The Specimen Data Manager will also develop, write, and maintain programmatic scripts with attention to accuracy, reproducibility, documentation, and maintainability.

The manager is responsible for fulfilling data requests in support of research activities, including identifying, preparing, integrating, validating, and delivering datasets from internal and external data sources. The position will investigate data validation errors, discrepancies, and data quality issues; identify items requiring resolution; and escalate decisions or issues requiring direction to the Director of Research Technology.

For specimen transfers, they support associated data activities, including querying data repositories to identify samples, reconciling and validating specimen data, preparing datasets and supporting documentation, and coordinating the transfer and integration of data and results into Memory and Aging Center systems. Questions or decisions requiring programmatic or technical direction will be brought to the Director of Research Technology.

They collaborate with Biospecimen Core leadership and other program stakeholders on domain-specific requirements and operational context to ensure data activities effectively support specimen operations and program needs.

In addition to Biospecimen Program responsibilities, the Specimen Data Manager serves a cross-functional role within the broader Data Core group. The position will contribute data management and technical support to other Data Core initiatives and needs as assigned, working across programs and projects to support data preparation, quality assurance, integration, reporting, and related data activities.

% of time	Essential Function (Yes/No)	Key Responsibilities (To be completed by Supervisor)
10	Yes	Maintains and develops research gathering, retrieval and reporting systems. Provide data extraction and reporting as needed for specimens billing including scripting, creating and maintaining Excel data sheets
5	Yes	Provides data feasibility input (e.g., cohort counts, availability) to support study design Works as part of team to support biospecimen requests through data querying and subject identification to provide to PI’s or Specimen Manager for design of a cohort
20	Yes	Prepares queries and reports for internal department constituents. Performs data querying and summary in support of data requests and routine reporting activities from internal and external researchers and clinicians for data requests outside supported/available Biospecimen data meta-repository.
10	Yes	Assists in maintaining systems for organizing data to analyze, identify and report trends. Implement/Modify scripts and queries to provide replicable pipeline for data return needs Functions as a data power user in key systems supporting biospecimen data workflows.
30	Yes	Aggregates and QC research specimen data; prepares and summarizes information and / or recommendations. Regularly (daily/weekly) requests, receives and integrates new inventory and biospecimen result datasets (csv/excel) into central data repositories. Checks all records for integrity of key identifiers, dates, and values with an emphasis on identifying, reporting, and assisting specimens team and laboratory staff in resolving any discrepancies.

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
• Working skills in analysis and consultation
• Skills to communicate complex information in a clear and concise manner both verbally and in writing
• 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
• Knowledge of Freezerworks LIMS or similar systems
• Ability to communicate complex information in a clear and concise manner both verbally and in writing.   Clear, concise communication style with easy going attitude
• Ability to multitask and be organized and work quickly in a dynamic environment with competing priorities
• 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

Preferred Qualifications

• Minimum of 3 years of research or clinical data management experience
• Knowledge of HIPAA and best practices for securing protected health information
• Experience working with relational databases or software tools to design queries and reports
• Basic understanding of genetics and proteomics