University of Chicago Company logo on Dataaxy
University of Chicago

Data Scientist/Engineer

πŸ“
Chicago, IL
πŸ§ͺ
Entry level
Department

MED - Biomedical Data Science - Beaulieu-Jones Research Staff

About The Department

The Section of Biomedical Data Science within the Department of Medicine at the University of Chicago performs research encompassing computational biomedicine, biomedical data science and biomedical informatics. The Beaulieu-Jones lab within the Section of Biomedical Data Science focuses on machine learning for healthcare within two primary areas: 1) Precision phenotyping of complex, heterogeneous conditions and, 2) Safe and Effective Deployment of Machine Learning in the clinic.

Job Summary

We are excited to offer a Data Scientist/Engineer position in the lab of Dr. Brett Beaulieu-Jones in the University of Chicago Department of Medicine. This role is ideal for individuals passionate about the application of machine learning to clinical data, specifically aiming to study the safe, equitable deployment of AI in the clinic. This position will be focused on translational applications and study of the integration of AI in healthcare. Strong candidates will have data science skills in addition to experience with data engineering in the context of healthcare. Candidates should be passionate about the rigorous evaluation of AI models for both performance and fairness across different populations.

Responsibilities

  • Develops and builds upon open source software for the monitoring of AI in the clinic.
  • Works closely with lab members and data scientists within the health system to support the study of model implementation.
  • Assists in the research, development and/or application of machine learning models to clinical data.
  • Participates in the evaluation and validation of developed models across multiple datasets and/or settings.
  • Supports lab efforts to publish research findings in scientific journals and/or present research findings at relevant scientific conferences and seminars.
  • Participates in lab activities including collaborative meetings, offering feedback to other members of the lab, literature review and preparing materials for research presentations.
  • 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.

Education:

Minimum Qualifications

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:

    Preferred Qualifications

    Education:

    • Advanced degree in computer science, data science, biomedical informatics or a related field.

    Technical Skills Or Knowledge:

    • Programming skills in Python or other languages commonly used for statistical programming (e.g., R).

    Preferred Competencies

    • Strong Analytical skills.
    • Problem-solving skills.
    • Organizational skills.
    • Verbal and written communication skills.
    • Work independently and as part of a team.

    Application Documents

    • Resume/CV (required)
    • Cover Letter (required)

    When applying, the document(s) MUST be uploaded via the My Experience page, in the section titled Application Documents of the application.

    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

    The University of Chicago is an Affirmative Action/Equal Opportunity/Disabled/Veterans and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, national or ethnic origin, age, status as an individual with a disability, military or 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.

    The University of Chicago's Annual Security & Fire Safety Report (Report) provides information about University offices and programs that provide safety support, crime and fire statistics, emergency response and communications plans, and other policies and information. The Report can be accessed online at: http://securityreport.uchicago.edu. Paper copies of the Report are available, upon request, from the University of Chicago Police Department, 850 E. 61st Street, Chicago, IL 60637.

    Key informations

    🧳
    Other
    πŸ“…
    Posted 4 months ago

    Don’t miss out on new
    Data & AI Jobs

    Get curated job alerts weekly.

    Other jobs at University of Chicago

    University of Chicago does not currently have any open job positions in Data & Ai.
    © 2023 | All Rights Reserved | Built with 🀍 in MontrealAll our data is gathered from publicly available sources or contributed by users