We are seeking a research data analyst that is interested in applying quantitative analytical methods to improve public health. Tuberculosis (TB) is the leading cause of death from an infectious disease worldwide, and innovative tools and approaches are needed to improve the diagnosis and care of individuals with TB infection and disease. This includes children, for whom there is a critical need to improve TB disease and infection detection. The Data Analyst will work with research scientists, c... more details
We are seeking a research data analyst that is interested in applying quantitative analytical methods to improve public health. Tuberculosis (TB) is the leading cause of death from an infectious disease worldwide, and innovative tools and approaches are needed to improve the diagnosis and care of individuals with TB infection and disease. This includes children, for whom there is a critical need to improve TB disease and infection detection. The Data Analyst will work with research scientists, clinicians, public health practitioners and collaborators both domestically and internationally to support the collection and analysis of a wide range of data types, including clinical, biological, digital, and real world data, in order to advance TB care locally and globally.
Current Major Projects Include:
Electronic health record (EHR)-based tools to support the latent TB infection (LTBI) care cascade for children in California. We have developed an EHR-based workflow to improve the screening, diagnosis and treatment of LTBI. The Data Analyst will evaluate any changes in outcomes after implementation of these tools by analyzing EHR data across multiple clinics, and will utilize these findings to guide the development of new interventions to improve and/or expand these tools. Skills of interest includes analysis of large datasets, and experience with analysis of EHR or real world data, or a strong interest to work with these data types.
The epidemiology and care cascade for Hepatitis B-TB co-infection. In partnership with collaborators from local public health departments and other regional health systems, we are examining the LTBI care cascade for individuals who are living with Hepatitis B and TB infection. Utilizing EHR, surveillance, and claims data, the Data Analyst will conduct the evaluation of the Hepatitis B-TB care cascade to guide interventions to improve the care of this vulnerable population. Skills of interest are similar to the child LTBI care cascade analyses.
Rapid Research in Diagnostics Development for TB Network (R2D2 TB Network) – This National Institutes of Health (NIH) U01-funded project established a multi-country platform for identifying promising early stage diagnostics from a broad range of product developers and conducting field evaluations in TB endemic countries to advance their development and evaluate their accuracy. This includes the evaluation of novel diagnostics in children (R2D2 Kids) and the role of digital diagnostics (i.e., cough sounds, lung sounds, chest x-ray images). The Data Analyst will work with other data analysts, data scientists and clinical research coordinators to support data collection, data management and accuracy analyses. Skills of interest include experience with REDCap, data management, and statistical computing (i.e., R, Stata, or Python).
Childhood ‘Omics’ and Mycobacterium tuberculosis-derived BiOsignatures (COMBO) for TB diagnosis in high HIV prevalence settings – This NIH R01-funded study seeks to identify novel biomarkers that can diagnose TB in children, utilizing retrospective and prospective cohorts in Uganda, South Africa, the Gambia, Peru and India. We will develop and validate combined host- and pathogen-based biosignatures using large ‘Omics-based datasets including proteomics and metabolomics, combined with clinical data. As needed, the Data Analyst will work with other data analysts, data scientists, and lab-based researchers to maintain the biorepository database and support analyses.
Progression of Tuberculosis infection in young children with and without HIV (PROTECT). This is an NIH-funded study that seeks to identify biomarkers that will predict if a child with evidence of TB exposure or infection will progression to symptomatic TB disease. Cross-sectional and serial biological samples from children from Uganda, South Africa, the Gambia, and Vietnam will be analyzed using high-throughput ‘Omics approaches including transcriptomics, proteomics, and metabolomics. As needed, the Data Analyst will work with other data analysts, data scientists, and lab-based researchers to maintain the biorepository database and support analyses.
The final salary and offer components are subject to additional approvals based on UC policy.
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Please note: An offer will take into consideration the experience of the final candidate AND the current salary level of individuals working at UCSF in a similar role.
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To learn more about the benefits of working at UCSF, including total compensation, please visit: https://ucnet.universityofcalifornia.edu/compensation-and-benefits/index.html
Master’s degree or PhD degree in Public Health or Data Science or equivalent experience
Experience working on health-related research projects
Skills in project management
Knowledge of medical terminology with a focus on the diagnosis of tuberculosis or other infectious diseases
Bachelor's degree in related area and / or equivalent experience / training
Minimum 3 years of related experience
Intermediate knowledge of data analysis methods, including summary statistics
Data formats: Must be able to manipulate wide range of data including clinical, demographic, electronic health record, and biological ‘Omics data, that is cross-sectional and longitudinal, or demonstrate a strong willingness to learn
Software
Intermediate experience in a statistical computing language including R, Python or Stata Experience with SQL or a strong willingness to learn
Proven skills and experience in independently resolving broad computing / data analysis problems
Self-motivated and works independently and as part of a team. Able to learn effectively and meet deadlines
Demonstrated experience and ability to collaborate effectively with all levels of staff; technical, students, faculty and administrators
Demonstrated ability to contribute research and technical content to peer-reviewed manuscripts, conference abstracts and/or grant proposals
Must be able to multi-task, work in a team, interact with clinicians, researchers and collaborators, communicate results (written, oral)
Must be interested in enabling health science through working on collaborative data analysis projects
Demonstrated effective communication and interpersonal skills. Demonstrated ability to communicate technical information to technical and non-technical personnel at various levels in the organization and to external research and education audiences
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