Bachelor's degree in a related field or equivalent experience
Advanced knowledge of clinical research methods and data management principles
Expertise in research database design and electronic data capture systems
Proficient in statistical software and data visualization tools
Ability to perform complex data analyses and prepare publication-quality reports
Experience in developing standardized data management workflows and quality control procedures
Strong communication skills for conveying complex information clearly
Responsibilities
Manage research data across multiple studies, ensuring integrity and compliance
Design and maintain research databases and data collection instruments
Establish standardized data management procedures across sites
Develop automated dashboards and study tracking systems
Analyze operational data to identify trends and recommend improvements
Prepare routine progress reports and present findings to stakeholders
Evaluate and implement emerging technologies to enhance research data systems
Benefits
Comprehensive training and development opportunities
Access to cutting-edge research technologies
Collaborative work environment with multidisciplinary teams
Opportunities for professional growth and advancement
Support for work-life balance initiatives
Full Job Description
Job Description
Job Summary:
The Data and Analytics Manager (DAM) position will oversee all aspects of the data operations of the Perinatal Research Program (PRP), and it is central to the continued growth and operational excellence of the Program.
The Perinatal Research Program (PRP) is organized around four major sub-program components with the mission of serving pregnant individuals and their families through excellence in clinical research.
Pregnancy Research Infrastructure and Support Management (PRISM) was established in 2010 to support research infrastructure within the Department of Obstetrics, Gynecology & Reproductive Sciences (OB/GYN & RS) at Mission Bay. To date, PRISM has supported over 50 studies, providing comprehensive, on-the-ground research support across the full spectrum of clinical research activities and serving multiple faculty Principal Investigators (PIs). A parallel infrastructure support program has been established at Zuckerberg San Francisco General Hospital (ZSFG), currently supporting an average of 5-6 studies and serving as a base to facilitate research participation and enrollment for UCSF faculty conducting clinical research at ZSFG.
The Maternal-Fetal Medicine Units (MFMU) Network collaboration was established at UCSF in 2023 under the leadership of the PRP Director. Originally founded in 1986, the MFMU Network conducts large-scale perinatal studies to improve maternal and fetal outcomes. Funded by the NIH Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), the network includes 14 clinical centers and a data coordinating center. PRP currently participates in three ongoing randomized clinical trials within the MFMU Network, with two additional trials anticipated to begin in 2026.
The Fetal Sequencing Program (FSP) represents another major component of PRP and positions UCSF as one of the national leaders in the field of perinatal genetics. Supported by NIH and philanthropic funding, this program provides advanced prenatal diagnostic services, including clinical exome and genome sequencing for a wide range of fetal conditions. FSP, with its multiple ongoing studies and extensive database also serves as a hub for UCSF learners (e.g. medical students, residents and fellows)
The fourth component, Perinatal Clinical Research (PRC), encompasses a diverse portfolio of studies funded by NIH, PCORI, philanthropy and industry sponsors. PRC includes large multicenter randomized controlled trials, long term follow up studies, industry sponsored studies, prenatal diagnostic development, and other treatment studies.
Collectively, the PRP portfolio includes approximately 25 active studies with total funding of approximately $7 million.
Responsibilities
of time
Essential Function (Yes/No)
Key Responsibilities
(To be completed by Supervisor)
30
YES
Research Data Management:
Independently manage research data across multiple PRP research studies, ensuring data integrity, security, and compliance with institutional, sponsor, and regulatory requirements.
Design, develop, implement, and maintain research databases, data dictionaries, data collection instruments, study protocols, and manuals of operations.
Establish standardized data management procedures to ensure consistency across multiple recruitment and collaborating sites.
Develop and maintain comprehensive documentation for all data management processes, including standard operating procedures (SOPs), data dictionaries, and version control.
Extract, transform, validate, clean, and prepare complex datasets for statistical analysis and reporting.
Provide technical consultation and ongoing support to investigators and study personnel regarding database design, data collection procedures, and data management best practices.
25
YES Research Study Monitoring and Evaluation
Collaborate with the PRP Director, Principal Investigators, and study teams to identify study monitoring, evaluation, and reporting requirements.
Design and implement monitoring frameworks and key performance indicators for multiple research studies.
Develop automated dashboards, recruitment reports, and study tracking systems to support operational oversight.
Prepare routine study progress reports and present findings during investigator meetings and project calls.
Analyze operational data to identify trends, recruitment challenges, protocol deviations, and workflow bottlenecks, providing recommendations for process improvement.
Support implementation and monitoring of research data security policies and institutional compliance requirements.
20
YES Data Analysis and Reporting
Independently prepare datasets for statistical analysis and conduct descriptive and analytical data analyses supporting research studies.
Generate data reports for grant applications, scientific presentations, manuscripts, abstracts, and regulatory reporting.
Prepare publication-quality tables, figures, charts, and summary reports for investigators and collaborators.
Summarize analytical findings and communicate study progress, milestones, and challenges to investigators and research leadership.
Recommend appropriate analytical methods and collaborate with investigators and biostatisticians to support study objectives.
10
YES Data Quality Assurance
Design, implement, and oversee comprehensive data quality assurance and quality control procedures.
Develop automated validation rules, quality assurance reports, and error-checking programs to ensure data completeness, accuracy, and consistency.
Monitor data quality across multiple studies and coordinate resolution of data discrepancies with study personnel.
Evaluate data management workflows and recommend improvements to increase efficiency and data reliability.
5
YES Training and Consultation
Develop and deliver training for research staff at UCSF and collaborating institutions on study databases, electronic data capture systems, and standardized data collection procedures.
Create user guides, training materials, and standard operating procedures for research personnel.
Provide consultation and technical support to investigators, research coordinators, students, interns, and research trainees regarding research data management and reporting systems.
5
YES Research Data Systems Innovation
Evaluate emerging technologies and recommend improvements to research data infrastructure and workflows.
Lead implementation of enhancements to electronic data capture systems and research databases to improve efficiency and support increasingly complex analyses.
Collaborate with the UCSF Epic team to optimize electronic health record (EHR) data extraction, cohort identification, and research workflows.
Evaluate and integrate Artificial Intelligence (AI) technologies to improve research operations, including automated patient screening, eligibility determination, chart abstraction, data extraction, dashboard development, and operational reporting.
Assess new software tools and technologies that improve data management, reporting, visualization, and research operations.
5
YES Professional Responsibilities
Independently plan and execute complex research data management and analytical activities for multiple concurrent studies.
Exercise independent judgment in resolving complex data management and analytical issues.
Collaborate effectively with investigators, clinical partners, statisticians, and multidisciplinary research teams.
Contribute to continuous quality improvement initiatives supporting PRP research operations.
Perform other duties as assigned by the supervisor.
100% (To update total %, enter the amount of time in whole numbers (without the % symbol - e.g., 15, 20) then highlight the total sum (e.g., 1%) at the bottom of the column and press F9. The total sum should add up to 100%.)
Qualifications
Required:
Bachelor's degree in related area and / or equivalent experience / training.
Advanced knowledge of clinical and translational research methods, research data management principles, human subjects protections, and applicable federal, state, sponsor, and institutional regulations (e.g., HIPAA, IRB, NIH, FDA, GCP).
Advanced knowledge of research database design, electronic data capture systems, relational databases, data governance, quality assurance/quality control, and research data security.
Demonstrated skill in extracting, integrating, validating, managing, analyzing, and reporting complex research and clinical datasets using statistical software, database query languages, and data visualization tools.
Demonstrated skill in designing and maintaining research databases, automated reports, dashboards, data dictionaries, standard operating procedures, and study documentation supporting multiple concurrent research studies.
Demonstrated ability to independently perform complex data analyses; prepare publication-quality reports, tables, figures, and summaries; and communicate analytical findings to investigators, collaborators, and research leadership.
Demonstrated ability to develop standardized data management workflows, quality control procedures, monitoring systems, and operational reporting processes that ensure data integrity, consistency, and regulatory compliance.
Demonstrated ability to provide technical consultation, training, and user support to investigators, research staff, and collaborating institutions regarding research databases, data collection procedures, and data management best practices.
Demonstrated ability to manage multiple concurrent projects, prioritize competing deadlines, exercise independent judgment, and collaborate effectively with multidisciplinary teams.
Skills to communicate complex information in a clear and concise manner both verbally and in writing.
Research skills at a level to evaluate evidence based alternate solutions and develop recommendations.
Preferred:
Masters degree in a related area
Experience to evaluate, implement, and optimize emerging technologies, including electronic health record (Epic) integrations, business intelligence tools, workflow automation, and Artificial Intelligence (AI) applications that improve research operations and data management.
Experience applying epidemiological methods to research data analysis.
