Biostatistician I
Announcement
Details
Open Date
09/08/2025
Requisition Number
PRN16363N
Job Title
Biostatistician I
Working Title
Biostatistician I
Job Grade
E
FLSA Code
Professional
Patient Sensitive Job Code?
No
Type
Non Benefited Staff / Student
Temporary?
No
Standard Hours per Week
20
Full Time or Part Time?
Part Time
Shift
Day
Work Schedule Summary
Monday - Friday from 9am to 1pm.
Is this a work study job?
No
VP Area
U of U Health - Academics
Department
00958 - DFPM-Administration
Location
Campus
City
Salt Lake City, UT
Type of Recruitment
External Posting
Pay Rate Range
$39,000 to $56,000 DOQ
Close Date
12/08/2025
Priority Review Date (Note - Posting may close at any time)
Job Summary
We are seeking a skilled and detail-oriented individual to join our team as a Part-Time Data Analyst in for the National Heart, Lung and Blood Institute (NHLBI) Advancing Research in Cardiovascular Health and Endometriosis Study (ARCHES). The Data Analyst, under guidance of team Principle and Co-Investigators, will be responsible for analyzing complex health-related data, with a focus on longitudinal data analysis, population databases, and causal inference.
Responsibilities
Data Cleaning and Preparation: Clean, validate, and prepare datasets for analysis, ensuring data quality and integrity. Handle missing data, outliers, and inconsistencies appropriately.
Statistical Modeling: Develop and apply appropriate statistical models to analyze complex health data, including regression models, survival analysis, hierarchical models, mediation analyses, validation work, and other relevant techniques with guidance from team Principal and Co-Investigators.
Longitudinal Data Analysis: With guidance from team Principal and Co-Investigators, conduct longitudinal data analysis using appropriate methods such as mixed-effects models, test for effect modification, and conduct formal mediation analyses.
Population Databases: Utilize population-level databases, such as electronic health records or Utah Population Database, to extract relevant information and perform statistical analysis.
Causal Inference: Apply causal inference methods to evaluate confounding in observational studies.
Data Visualization: Generate clear and informative data visualizations, graphs, and charts to present analytical findings and facilitate understanding by both researchers and the lay public.
Quality Assurance: Ensure accuracy and reliability of analysis results by conducting rigorous quality assurance checks and validating analytical outputs.
Collaboration and Communication: Collaborate effectively with interdisciplinary teams, including researchers, clinicians, and other data analysts. Clearly communicate analysis methods, results, and implications to both technical and non-technical audiences.
Machine Learning (Plus): Utilize machine learning techniques to analyze health outcome data, develop predictive models, and identify patterns and trends in large datasets.
Work Environment and Level of Frequency typically required
Nearly Continuously: Office environment.
Physical Requirements and Level of Frequency that may be required
Nearly Continuously: Sitting, hearing, listening, talking.
Often: Repetitive hand motion (such as typing), walking.
Seldom: Bending, reaching overhead.
Minimum Qualifications
This position requires familiarity with standard statistical analysis procedures with a minimum of a BS degree in statistics, biostatistics, a related field, or equivalency (one year of education can be substituted for two years of related work experience); General programming skills or familiarity with at least one statistical programming language such as SAS or R with the ability to independently gain new skills and solve difficult programming challenges; Experience with Microsoft Office (Word, Excel, PowerPoint) is necessary; An ability to work on several projects simultaneously and manage deadlines, and good communication skills.
Preferences
• Education: Bachelor's degree in a relevant field (e.g., statistics, epidemiology, biostatistics, public health) or equivalent experience. Master's degree is a plus.
• Experience: Minimum of 2-3 years of experience in statistical data analysis, preferably in a health sciences or healthcare setting.
• Longitudinal Data Analysis: Strong understanding and practical experience with longitudinal data analysis methods, including mixed-effects models.
• Population Databases: Familiarity with large-scale population-level databases, such as electronic health records, Utah Population Database, or administrative claims databases.
• Causal Inference: Knowledge of causal inference methods (e.g., directed acyclic graphs), mediation analyses, and related techniques to address confounding factors in observational studies and assessment of direct and indirect effects.
• Machine Learning (Plus): Experience with machine learning techniques and tools for health outcome research, including classification, regression, clustering, and deep learning algorithms.
• Statistical Software: Proficiency in statistical software such as SAS, Stata, R or Python, including relevant packages for data manipulation, visualization, and statistical modeling.
• Data Management: Strong data management skills, including data cleaning, merging, and transformation.
• Analytical Thinking: Strong analytical and problem-solving skills, with the ability to approach complex research questions and data challenges.
• Communication Skills: Excellent written and verbal communication skills, with the ability to convey technical concepts to both technical and non-technical stakeholders.
• Time Management: Ability to manage multiple projects, prioritize tasks, and meet deadlines in a fast-paced environment.
Special Instructions Summary
Additional Information
The University is a participating employer with Utah Retirement Systems ("URS"). Eligible new hires with prior URS service, may elect to enroll in URS if they make the election before they become eligible for retirement (usually the first day of work). Contact Human Resources at [click to reveal phone number] for information. Individuals who previously retired and are receiving monthly retirement benefits from URS are subject to URS' post-retirement rules and restrictions. Please contact Utah Retirement Systems at [click to reveal phone number] or [click to reveal phone number] or University Human Resource Management at [click to reveal phone number] if you have questions regarding the post-retirement rules.
This position may require the successful completion of a criminal background check and/or drug screen.
The University of Utah values candidates who have experience working in settings with students and patients from all backgrounds and possess a strong commitment to improving access to higher education and quality healthcare for historically underrepresented students and patients.
All qualified individuals are strongly encouraged to apply. Veterans' preference is extended to qualified applicants, upon request and consistent with University policy and Utah state law. Upon request, reasonable accommodations in the application process will be provided to individuals with disabilities.
The University of Utah is an Affirmative Action/Equal Opportunity employer and does not discriminate based upon race, ethnicity, color, religion, national origin, age, disability, sex, sexual orientation, gender, gender identity, gender expression, pregnancy, pregnancy-related conditions, genetic information, or protected veteran's status. The University does not discriminate on the basis of sex in the education program or activity that it operates, as required by Title IX and 34 CFR part 106. The requirement not to discriminate in education programs or activities extends to admission and employment. Inquiries about the application of Title IX and its regulations may be referred to the Title IX Coordinator, to the Department of Education, Office for Civil Rights, or both.
To request a reasonable accommodation for a disability or if you or someone you know has experienced discrimination or sexual misconduct including sexual harassment, you may contact the Director/Title IX Coordinator in the Office of Equal Opportunity and Affirmative Action (OEO/AA). More information, including the Director/Title IX Coordinator's office address, electronic mail address, and telephone number can be located at: [click to reveal website link]
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