Pittsburgh, , United States
GSPH-Epidemiology - Pennsylvania-Pittsburgh - (23008579)
Provides subject matter expertise in data manipulation, statistical data methodologies, data analysis, and development of new data science methods. Collaborates with principal investigators or study sponsors on high-level study design, data collection, data set analysis, protocol development, statistical analysis and inference, and report writing and presentations for internal and external audience. Leads development of complex analytical plans, creates systems for data monitoring, provides high-level statistical support, utilizes statistical software, creates research study reports, and contributes to manuscripts, grants, and scientific presentations. Adheres to all protocols.
The University of Pittsburgh is committed to championing all aspects of diversity, equity, inclusion, and accessibility within our community. This commitment is a fundamental value of the University and is crucial in helping us advance our mission, which includes attracting and retaining diverse workforces. We will continue to create and maintain an environment that allows individuals to discover, belong, contribute, and grow, while honoring the experiences, perspectives, and unique identities of all.
The University of Pittsburgh is an Affirmative Action/Equal Opportunity Employer and values equality of opportunity, human dignity and diversity. EOE, including disability/vets.
The University of Pittsburgh requires all Pitt constituents (employees and students) on all campuses to be vaccinated against COVID-19 or have an approved exemption. Visit hr.pitt.edu/contact-ohr to learn more.
Assignment Category Full-time regular
Job Classification Staff.Data Scientist IV
Job Family Research
Job Sub-Family Data Science
Minimum Education Level Required Master's Degree
Minimum Years of Experience Required 9
Will this position accept substitution in lieu of education or experience? Combination of education and relevant experience will be considered in lieu of education and/ or experience requirement.
Work Schedule 8:30 am - 5:00 pm, M-F
Work Arrangement Remote: Teams working from different locations (off-campus).
Hiring Range TBD Based Upon Qualifications
Relocation Offered No
Visa Sponsorship Provided No
Background Check For position finalists, employment with the University will require successful completion of a background check
Child Protection Clearances Not Applicable
Required Documents Resume, Cover Letter
Optional Documents Not Applicable
Essential Functions The data scientist will collaborate on designing studies using existing observational data; implementing statistical analyses; and interpreting results. The researcher will take a lead role in writing and executing code for the statistical analyses. The datasets used by this research line include large, longitudinal datasets; multilevel datasets; and triangulation and integration of datasets arising from multiple sources. Pending successful completion of the appropriate background checks, the researcher will join the research team for the Longitudinal Study of Handgun Ownership and Transfers (LongSHOT), a cohort study of the impact of handgun ownership on mortality risks in over 35 million individuals followed longitudinally for over 17 years. More information on the design of LongSHOT can be found here: https://pubmed.ncbi.nlm.nih.gov/32492303/. LongSHOT projects will begin with a focus on quantifying the effects of firearm-related policies (e.g., extreme risk protection orders; waiting periods) on suicide and homicide risks in specific populations.
Physical Effort Generally sedentary.