Biomedical Data Statistician, Technical Assistant

About the role

The Duchossois Family Institute (DFI) at the University of Chicago 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. This role involves providing technical support for statistical design and implementation of research analysis, utilizing knowledge of statistics to communicate analyses for research proposals and drafting reports detailing results.

Responsibilities

• Apply foundational knowledge in probability, variance, hypothesis testing, regression analysis, experimental design, and statistical programming languages, particularly R and Python (including libraries like pandas or NumPy).
• Utilize SQL skills for querying, cleaning, and merging large datasets from relational databases.
• Select, transform, and create data variables to improve the accuracy of predictive models.
• Create insightful dashboards and charts using visualization tools such as Tableau or Power BI.
• 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).
• Support the creation and maintenance of data models, databases, and software applications.
• Assists in the production, presentation, and discussion of high-quality data analysis reports for audiences.
• Participate in the dissemination of research findings through scientific publications.
• With high levels of researcher guidance, assist in developing objectives, designing sampling, randomization, and data collection procedures to achieve study objectives.
• Analyzes 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.

Requirements

• Minimum requirements include vocational training, apprenticeships, or the equivalent experience in related field (not typically required to have a four-year degree).
• Knowledge and skills developed through < 2 years of work experience in a related job discipline.

Preferred Qualifications

• Experience practical knowledge of supervised and unsupervised learning algorithms like decision trees, random forests, and clustering.
• Experience working with biomedical and computational datasets to build custom inward and outward facing applications with advanced AI/ML approaches and robust visualization.
• Experience building large-scale web applications and using statistical packages/software to analyze multi-modal microbiome research data.
• Hands-on experience implementing supervised and unsupervised machine learning algorithms, including decision trees, random forests, and clustering techniques.
• Basic understanding of connecting to and retrieving data from AI models via REST APIs (e.g., OpenAI or Hugging Face) and Agentic AI concepts.
• Working knowledge of relational databases (e.g. MySQL, Postgres) and UI/UX design.
• Experience leveraging HPC/Cloud computing and distributed architectures.
• Proven ability in conducting unit and integration testing for applications and algorithms.