Research Data Manager at University of California San Francisco

JOB SUMMARy

We are in the midst of a massive, data-driven transformation in medicine. Driven by the push for streamlined drug development, the market for advanced analytics and AI in clinical research is expanding exponentially.

The PReDiCTR-TB Consortium is not just following industry standards—we are creating and leading them. Our work focuses on radical TB drug development data integration, utilizing cutting-edge computational and AI-driven approaches to advance drug development and precision dosing for infectious diseases and vulnerable special populations.

We are moving past the static, isolated spreadsheets of the past. To power the next generation of machine learning models and Drug-Informed Drug Development, we need a solution-minded, highly organized Research Data Manager/Database Administrator. You will be the architect of our data liquidity, designing and maintaining the data systems that turn complex, raw data into a structured, scalable asset for global research collaborators.

Department Overview

The Savic Integrated Pharmacology Laboratory in the Department of Bioengineering and Therapeutic Sciences at the University of California, San Francisco (UCSF) is a global leader in model-informed drug development (MIDD) for infectious diseases and serves as an innovation hub for translational pharmacology, quantitative systems pharmacology (QSP), pharmacometrics, machine learning, artificial intelligence, and mechanistic modeling. The laboratory develops and applies cutting-edge computational and quantitative approaches to accelerate the discovery and optimization of treatment regimens for tuberculosis (TB), HIV, malaria, pediatric infectious diseases, and other conditions impacting global health. As the coordinating center for the international Preclinical Design and Clinical Translation of Regimens for Tuberculosis (PReDiCTR-TB) Consortium, the laboratory integrates computational science, predictive modeling, translational pharmacology, clinical data, and quantitative decision science to support regimen selection, dose optimization, clinical trial design, and model-informed decision-making across the drug development lifecycle. The Savic Lab fosters a highly collaborative, interdisciplinary, and collegial research environment where pharmacometricians, computational scientists, data scientists, engineers, clinicians, and biologists work together with academic, government, nonprofit, and industry partners worldwide to solve complex translational challenges and translate scientific discoveries into improved patient outcomes.

Required Qualifications

• Bachelor's degree in related area and / or equivalent experience / training.
• Minimum 3 years of hands-on experience in database design, data pipeline engineering, and data harmonization or related experience
• Technical Stack: Strong programming and querying skills across languages like SQL and Python or R (familiarity with tools like Stata, SAS or NONMEM data structures is a major plus).
• Environment: Direct experience working within research data environments, ideally supporting large-scale, NIH/state-funded programs.
Communication: Exceptional communication skills with the ability to collaborate effectively across interdisciplinary teams of software engineers, pharmacometricians, and clinical investigators

Preferred Qualifications

• Master’s degree in Data Science, Computer Science, Bioinformatics, Health Informatics, or a closely related quantitative field.
• Prior experience navigating the data complexities of academic medical centers, consortia, or collaborative international research settings.
• Familiarity with clinical data ontologies and common data models (e.g., OMOP, CDISC, LOINC, or FHIR transfer protocols).