Data Scientist

University of Chicago•Hyde Park, IL

13d•Onsite

About The Position

The Data Scientist will lead data science research efforts within the breast cancer program in the Section of Hematology/Oncology in the Department of Medicine. The Section of Hematology/Oncology has a proud and long tradition of excellence in research-based patient care and clinical discovery. Ranked among the finest cancer programs in the country, the Section is comprised of nationally and internationally known faculty with expertise in all major types of malignancies, blood disorders, and experimental therapies.

Requirements

Minimum requirements include a college or university degree in related field.
Minimum requirements include knowledge and skills developed through 2-5 years of work experience in a related job discipline.

Nice To Haves

Advanced degree in computer science.
Experience in python including torch and scikit-learn libraries strongly preferred.
Experience in working with image data or unstructured text data with large language models.
Proficiency in Linux/Ubuntu OS including basic file and user management, ssh.
Familiarity with tmux, SLURM.
Strong Analytical skills.
Problem-solving skills.
Organizational skills.
Verbal and written communication skills.
Ability to work independently and as part of a team.

Responsibilities

Manage the program’s projects.
Develop frameworks for housing multi-modal clinical data – including genomic, pathology, and radiographic imaging data.
Develop and code data dictionaries for discrete data.
Write, Implement, and develop efficient code and machine learning tools and pipelines for data processing and analysis.
Work with collaborators to implement emerging external computational tools for program data.
Draft grant proposals.
Develop training material.
Keep lab's knowledge-based trainings up to date.
Supervise trainees.
Perform reproducible genomic data analysis.
Calibrates data between large and complex research and administrative datasets.
Guides and may set the operational protocols for collecting and analyzing information from the University's various internal data systems as well as from external sources.
Designs and evaluates statistical models and reproducible data processing pipelines using expertise of best practices in machine learning and statistical inference.
Provides expertise for high level or complex data-related requests and engages other IT resources as needed.
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.