Statistician And Data Scientist

The Division of HIV, Infectious Diseases and Global Medicine at Zuckerberg San Francisco General Hospital and Trauma Center (ZSFG) is an internationally recognized global leader in HIV clinical care, research and education and has grown to encompass a network of specialty clinics, multiple research and clinical trials, an HIV education program, an international research program in East Africa and a vibrant community forum for clinicians and researchers. Housed within the Division is the SCOPE (Study on Consequences of the Protease Inhibitor Era and LIINC (Long-term Impact of Infection with the Novel Coronavirus) Research Programs that focuses on clinical and translational research.

The Data Scientist/Statistician (Research Data Analyst 3) will be responsible for working with a study team of Faculty, Clinical Research Coordinators, Study Managers, and administrative analysts to apply statistical and Data science methodologies to original research projects that focus on HIV and SARS-CoV-2 infection and effects on health. They will also complete data requests and biospecimen requests to support the overall project. The successful candidate will have the ability to work with a variety of data sources, including administrative and longitudinal survey data and will be able to clean, manage, link, and analyze these sources. They will be passionate about using data to support strategies for a cure in multiple infectious disease conditions, particularly HIV and Long Covid (LC). The incumbent will be able to conduct analyses and Data management on multiple projects concurrently across both research portfolios. We seek a highly organized individual with outstanding statistical analysis and Data management skills who has superior written and verbal communications skills and excellent time management. The Data Scientist/Statistician will:

• Report to the Study PIs and Program Managers of the LIINC and SCOPE research program and work closely with other analysts. The incumbent will work collaboratively with other investigators, trainees, staff, and partner organizations.
• Determine data sources for gathering available data – including but not limited to study-specific databases for SCOPE, LIINC, and the relevant substudies and clinical trials, as well as data from the national RECOVER study database, local and national biorepository databases, and public health data if applicable.
• Plan and design data management and Data analysis of multiple studies.
• In consultation with program managers and principal investigators, develop multivariable data analysis plans, using appropriate statistical methods. The Data Scientist/Statistician should be able to carry out the analysis plan independently.
• Provide statistical input into development of data collection tools, including questionnaires.
• Document processes to ensure accuracy and outcomes of research.
• Evaluate inconsistencies and trends in the data and present hypotheses related to the implications in the analysis.
• Present findings to PI and incorporate the feedback into additional iterations of the report.
• Provide statistical expertise to PI.
• Design processes to guarantee strict privacy of data.
• Provide documentation, including drafting statistical sections of grant proposals, manuscripts and reports.
• Develop systems to allow data to be used adhering to data use agreement.
• Contribute to study design, ensure the data necessary to evaluate study hypotheses are collected, and the resulting datasets are of sufficient quality to provide reliable results.
• Collaborate with investigators on research papers.
• (Preferred) Create presentations of data using data visualization software.
• (Preferred) Experience (e.g., content knowledge) with the nuances of infectious disease datasets, in particular HIV datasets and phenotypes, and Long Covid datasets and phenotypes.
• (Preferred) Familiarity with NIH databases such as the Seven Bridges platform.

This position requires extensive experience conducting statistical analysis of observational studies, program evaluations, administrative datasets, and longitudinal cohorts.
The final salary and offer components are subject to additional approvals based on UC policy.
To see the salary range for this position (we recommend that you make a note of the job code and use that to look up): TCS Non-Academic Titles Search (https://tcs.ucop.edu/non-academic-titles)
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.
For roles covered by a bargaining unit agreement, there will be specific rules about where a new hire would be placed on the range.
To learn more about the benefits of working at UCSF, including total compensation, please visit: https://ucnet.universityofcalifornia.edu/compensation-and-benefits/index.html

REQUIRED QUALIFICATIONS

• Bachelor’s degree in statistics or related area (e.g., biomedical sciences) and / or equivalent experience / training.
• Minimum 3+ years of related experience
• 3 or more years of experience in a related field / with relevant research experience.
• Thorough skills in programming, statistical analysis and Data management in STATA, SAS or R.
• Substantive knowledge of quantitative research methods.
• Research skills at a level to evaluate alternate solutions and develop recommendations.
• Extensive experience conducting statistical analysis of observational studies, program evaluations, administrative data or longitudinal cohorts.
• Strong skills in project management.
• Ability to work discreetly with sensitive and confidential data.
• Ability to multi-task with demanding timeframes.
• Ability to work independently and as part of a team.
• Skills to communicate complex information in a clear and concise manner both verbally and in writing.

PREFERRED QUALIFICATIONS

• Graduate degree in statistics, epidemiology or related area and / or equivalent experience / training.
• Familiarity with NIH databases such as the Seven Bridges platform.
• Experience (e.g., content knowledge) with the nuances of infectious disease datasets, in particular HIV datasets and phenotypes, and Long Covid datasets and phenotypes.
• Knowledge of data visualization software.

• Report to the Study PIs and Program Managers of the LIINC and SCOPE research program and work closely with other analysts. The incumbent will work collaboratively with other investigators, trainees, staff, and partner organizations.
• Determine data sources for gathering available data – including but not limited to study-specific databases for SCOPE, LIINC, and the relevant substudies and clinical trials, as well as data from the national RECOVER study database, local and national biorepository databases, and public health data if applicable.
• Plan and design data management and Data analysis of multiple studies.
• In consultation with program managers and principal investigators, develop multivariable data analysis plans, using appropriate statistical methods. The Data Scientist/Statistician should be able to carry out the analysis plan independently.
• Provide statistical input into development of data collection tools, including questionnaires.
• Document processes to ensure accuracy and outcomes of research.
• Evaluate inconsistencies and trends in the data and present hypotheses related to the implications in the analysis.
• Present findings to PI and incorporate the feedback into additional iterations of the report.
• Provide statistical expertise to PI.
• Design processes to guarantee strict privacy of data.
• Provide documentation, including drafting statistical sections of grant proposals, manuscripts and reports.
• Develop systems to allow data to be used adhering to data use agreement.
• Contribute to study design, ensure the data necessary to evaluate study hypotheses are collected, and the resulting datasets are of sufficient quality to provide reliable results.
• Collaborate with investigators on research papers.
• (Preferred) Create presentations of data using data visualization software.
• (Preferred) Experience (e.g., content knowledge) with the nuances of infectious disease datasets, in particular HIV datasets and phenotypes, and Long Covid datasets and phenotypes.
• (Preferred) Familiarity with NIH databases such as the Seven Bridges platform