The University Of Chicago
* Leads the acquisition, cleaning, and harmonization of secondary datasets from the multiple sources, including international cohort studies, with support from Dr. Farina and the project team.* Conducts data exploration and statistical analyses to extract meaningful insights from large, complex datasets, with support from Dr. Farina, Dr. Capuano and the project team.* Unify different types of data including cognitive instruments (e.g., MMSE, MoCA, Trails, Digit Symbol, HVLT, etc.): perform measurement invariance testing; build IRT/linking models and score crosswalks; document comparability limits.* Correct site/batch effects and temporal drift using mixed-effects models, empirical Bayes approaches, and sensitivity analyses.* Handle missing with principled methods (e.g., MICE, IPW); quantify robustness.* Maintain privacy-conscious data handling (HIPAA/GDPR concepts).* Maintains and analyzes statistical models using best practices in machine learning, statistical inference, and reproducible research workflows.* Prepares publication-ready tables, figures, and statistical summaries for interim and final reports.* Develops tailored statistical procedures and visualizations for specific research questions.* Analyzes moderately complex data sets for the purpose of extracting and purposefully using applicable information.* Provides professional support to staff or faculty members in defining the project and applying principals of data science in manipulation, statistical applications, programming, analysis and modeling.* Cleans, transforms, merges, and matches between large and complex research and administrative datasets. Plans own resources to collect, organize, and analyze information from the University's various internal data systems as well as from external sources.* Builds and analyzes statistical models and reproducible data processing pipelines using knowledge of best practices in machine learning and statistical inference. Serves as a single point of contact for all requests and engages other IT resources to assist.* Performs other related work as needed.* Foundational knowledge and hands-on practice in core statistical methods – descriptive inference, probability, linear/logistic regression – with implementation in R/Python and clear interpretation.* Hands-on experience harmonizing cognitive assessment data and applying measurement invariance/IRT/score linking.* Practical knowledge of missing data (MICE, weighting).* Experience publishing harmonized datasets and reproducible reports (R Markdown/Quarto/Jupyter).* Foundational knowledge and hands-on practice in survival analysis, mixed-effects models and longitudinal modeling.* Experience with health data standards (ICD, SNOMED, LOINC, HL7 FHIR or OMOP) and unit/scale conversions (UCUM).* Excellent written and oral communication.* Organization.* Problem-solving.* Collaboration.* Attention to detail.* Able to work autonomously.* Skills with a wide variety of digital collaboration tools (Zoom, MS Teams, etc.).* Proficiency in MS Office Suite.* Programming and Coding experience.* Ability to use a computer for extended periods.* Office/Clinical Setting.When applying, the document(s) **MUST** be uploaded via the **My Experience** page, in the section titled **Application Documents** of the application.The University of Chicago is an urban research university that has driven new ways of thinking since 1890. Our commitment to free and open inquiry draws inspired scholars to our global campuses, where ideas are born that challenge and change the world.We empower individuals to challenge conventional thinking in pursuit of original ideas. Students in the College develop critical, analytic, and writing skills in our rigorous, interdisciplinary core curriculum. Through graduate programs, students test their ideas with UChicago scholars, and become the next generation of leaders in academia, industry, nonprofits, and government.To learn more about the university click here
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