Department
BSD DFI - Translational Informatics
About the Department
The Duchossois Family Institute (DFI) at the University of Chicago is using cutting-edge technologies and developing facilities to accelerate research and introduce novel interventions that optimize microbiome-mediated host defenses, with the goal of enhancing health. By developing new knowledge about the interactions between the human body and the microbiome, the DFI is breaking new ground that will lead to therapies that increase resistance to a wide range of diseases.
Job Summary
The job provide basic technical support activities related to the statistical design and implementation of research analysis. Uses knowledge of statistics to communicate analyses for research proposals and draft reports detailing their results. Follows objectives and procedures for sampling, randomization, data collection, analysis, and quality control.
The Duchossois Family Institute (DFI) is seeking a part-time Biomedical Data Statistician Technical Assistant to support the development of scalable analytical applications for managing and analyzing large biomedical datasets. Working within the Translational Informatics team, the successful candidate will leverage modern technologies to organize, integrate, and extract insights from complex data. Ideal candidates will have experience with web frameworks, APIs, databases, data visualization tools, and back-end programming languages, as well as the ability to contribute across the technology stack.
Responsibilities
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Apply foundational knowledge in probability, variance, hypothesis testing, regression analysis, experimental design, and in statistical programming languages, particularly R and Python (including libraries like pandas or NumPy).
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Utilize SQL skills for querying, cleaning and merging large datasets from rational databases.
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Assist in the development, testing, and optimization of prompts to extract structured, accurate data from Large Language Models, working collaboratively under direct supervision.
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Select, transform, and create data variables to improve the accuracy of predictive models.
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Assist to create insightful dashboards and charts using visualization tools such as Tableau or Power BI.
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Contribute to the development of data algorithms and specialized computer software for identifying and classifying components of biological systems (such as DNA and protein sequences).
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Support the creation and maintenance of data models, databases, and software applications.
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Assists in the production, presentation, and discussion of high-quality data analysis reports for audiences.
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Participate in the dissemination of research findings through scientific publications.
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Relies on administrative guidance and review, collaborates with researchers in designing, implementing, and monitoring research.
With high levels of researcher guidance assists in developing objectives, designing sampling, randomization, and data collection procedures to achieve study objectives.
Assists analyzing data and prepares tables for interim and final reports. May help design tables and statistical procedures for specific research studies.
Maintains collaboration with other research support personnel, including analysts and programmers in monitoring and assessing data quality.
Performs other related work as needed.
Minimum Qualifications
Education:
Minimum requirements include vocational training, apprenticeships or the equivalent experience in related field (not typically required to have a four-year degree).
Work Experience:
Minimum requirements include knowledge and skills developed through < 2 years of work experience in a related job discipline.
Certifications:
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Preferred Qualifications
Experience:
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Practical knowledge of supervised and unsupervised learning algorithms like decision trees, random forests, and clustering.
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Experience working with biomedical and computational datasets to build custom inward and outward facing applications with advanced AI/ML approaches and robust visualization.
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Experience building large-scale web applications and using statistical packages/software to analyze multi-modal microbiome research data.
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Hands-on experience implementing supervised and unsupervised machine learning algorithms, including decision trees, random forests, and clustering techniques.
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Basic understanding of connecting to and retrieving data from AI models via REST APIs (e.g., OpenAI or Hugging Face) and Agentic AI concepts.
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Working knowledge of relational databases (e.g. MySQL, Postgres) and UI/UX design.
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Experience leveraging HPC/Cloud computing and distributed architectures.
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Proven ability in conducting unit and integration testing for applications and algorithms.
Preferred Competencies
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Demonstrated excellence in debugging and optimizing code and workflows.
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Ability to collaborate effectively with students, postdoctoral fellows, and academic faculty members.
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Strong attention to detail.
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Flexible and adaptable, able to deliver analyses under tight deadlines for grant applications or presentations.
Working Conditions
Application Documents
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Resume (required)
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Cover Letter (preferred)
The University of Chicago uses AI-assisted tools to streamline and augment some recruitment processes; however, AI is not used to make hiring decisions.
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
Scheduled Weekly Hours
30
Drug Test Required
No
Health Screen Required
No
Motor Vehicle Record Inquiry Required
No
Pay Rate Type
Hourly
FLSA Status
Non-Exempt
Pay Range
$19.23 - $26.44
The included pay rate or range represents the University’s good faith estimate of the possible compensation offer for this role at the time of posting.
Benefits Eligible
Yes
The University of Chicago offers a wide range of benefits programs and resources for eligible employees, including health, retirement, and paid time off. Information about the benefit offerings can be found in the Benefits Guidebook.
Posting Statement
The University of Chicago is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, or expression, national or ethnic origin, shared ancestry, 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.
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.
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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