Department

BSD MED - Pulmonary - Parker Research Staff
About the Department

Dr. William Parker’s Healthcare Ethics and Allocation Laboratory (HEAL) in the Section of Pulmonary & Critical Care Medicine.
Job Summary

The Data Scientist will work in collaboration with Dr. Parker, a medical ethicist and health services researcher who studies the allocation of scarce medical resources. He is specifically interested in absolute scarcity problems, where demand greatly exceeds supply, and healthcare systems cannot avoid triage scenarios. He applies advanced empirical methods to evaluate and design allocation systems according to the underlying ethical principles. His current projects focus on deceased donor organ allocation, critical care/ventilator rationing under crisis standards of care, and COVID-19 vaccine allocation.

The position will focus on the development and execution of complex data analyses and modeling projects. Databases include electronic health record datasets and national transplant registries.

In collaboration with Dr. Parker, they will participate as a skilled individual contributor and/or lead researcher, contributing his/her high-level expertise to each project’s development. 

Responsibilities

• Data cleaning and management.
• Prepares analytic datasets using data analysis software (E.g. R tidyverse packages, Pandas for Python).
• Follows the standards of transparent and reproducible data science including use version control software such as git and code with a literate programming style.
• Anticipates data management needs, including identifying when data pulls will be necessary and obtaining newer versions of source national datasets.
• Data visualization with appropriate statistical software, such as the ggplot2 package in R.
• Fits complex statistical models with appropriate statistical software, such as R or Stata.
• Trains, tunes, and tests machine learning prediction models with appropriate statistical software, such as scikit-learn, tensor flow, or pytorch packages.
• Investigates and apply new data science methodologies to projects.
• Reports results of data analysis, prepare figures and tables.
• Draft and revise manuscripts for submission.
• Prepares grant proposals.
• Supervise medical students and other junior trainees.
• Present research findings at meetings.
• 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.
• Performs other related work as needed.

Minimum Qualifications

Education:

Minimum requirements include a college or university degree in related field.---
Work Experience:

Minimum requirements include knowledge and skills developed through 2-5 years of work experience in a related job discipline.---
Certifications:

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Job Family

Research
Role Impact

Individual Contributor
FLSA Status

Exempt
Pay Frequency

Monthly
Scheduled Weekly Hours

40
Benefits Eligible

Yes
Drug Test Required

No
Health Screen Required

No
Motor Vehicle Record Inquiry Required

No
Posting Statement

Employees must comply with the University’s COVID-19 vaccination requirements. More information about the requirements can be found on the University of Chicago Vaccination GoForward.

The University of Chicago is an Affirmative Action/Equal Opportunity/Disabled/Veterans Employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national or ethnic origin, age, status as an individual with a disability, protected veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice of Nondiscrimination.

Staff Job seekers in need of a reasonable accommodation to complete the application process should call 773-702-5800 or submit a request via Applicant Inquiry Form.

We seek a diverse pool of applicants who wish to join an academic community that places the highest value on rigorous inquiry and encourages a diversity of perspectives, experiences, groups of individuals, and ideas to inform and stimulate intellectual challenge, engagement, and exchange.

All offers of employment are contingent upon a background check that includes a review of conviction history.  A conviction does not automatically preclude University employment.  Rather, the University considers conviction information on a case-by-case basis and assesses the nature of the offense, the circumstances surrounding it, the proximity in time of the conviction, and its relevance to the position.

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