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Responsibilities*

Refine, adapt and apply advanced statistical modeling techniques to analyze complex datasets including longitudinal data, functional data, geographically referenced data.  

Conduct statistical analyses using established/routine statistical methods Write, test, and implement statistical programming code to clean, merge, process complex, large datasets including creating variables based on questionnaire data, longitudinal data, functional data, geographically referenced data

Prepare and maintain documentation of data cleaning and analysis  

Lead and/or participate in writing research publications, including literature reviews, drafting/editing sections of articles

Collaborate with research group members by providing feedback on research tasks and projects.

Organize, participate and/or lead research group meetings among research group and be liaison with researchers in collaborating departments 

Required Qualifications*

* MS degree in Biostatistics, Statistics, or related field.  

* Expertise in R, Python, C++ programming languages.

* Familiarity with Bayesian and causal inference.

* Documented experience in writing research articles.

* Ability to prioritize, organize and work efficiently on multiple projects

* Ability to work independently and work in teams

* Excellent communication skills * 2 or more years experience in data analysis

* 2 or more years experience managing/cleaning/processing big datasets. 

Desired Qualifications*

*GIS experience

*Experience handling datasets with millions of records

Additional Information

The Biostatistics for Social Impact (B4SI) Laboratory is seeking a full-time statistician. The selected applicant will be part of a growing biostatistics research lab focusing on biostatistical research and collaborative research involving social and environmental determinants of health. This individual will collaborate on 2-3 projects involving researchers in UM and other institutions partnering with the B4SI Lab. Opportunities for career advancement include working on cutting-edge biostatistical methods for large complex datasets, co-authoring research papers, and may additionally include attending research conferences and travel to collaborating institutions.  The ideal candidate is dynamic, creative, self motivated, and has excellent problem solving skills.

This position is term limited to 1 year, given funding limitations, with possibility of extension depending on additional grant funding. Position may be under-filled depending on applicant pool.  

We are seeking an experienced and dynamic staff leader/member with a commitment to contributing to a diverse, equitable and inclusive environment for all members of our community.

Background Screening

The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks. Background checks will be performed in compliance with the Fair Credit Reporting Act.

U-M EEO/AA Statement

The University of Michigan is an equal opportunity/affirmative action employer.