Data Scientist, AI for Healthcare & Translation

University-of-Illinoi; Chicago (IL); On-site; USD 100,000 - 130,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Life Insurance

Retirement Plan

Paid time off

Tuition waivers for employees and/or;/

Job summary

University of Illinois Chicago is seeking a Data Scientist to lead and contribute to AI/ML research advancing healthcare delivery and clinical decision-making. The role integrates data science, software engineering, and translational research with a focus on reproducibility and real-world impact.

You will collaborate with faculty, clinicians, and data engineers, mentoring junior researchers and helping build scalable, secure computing environments in alignment with institutional policies.

Qualifications

• Ph.D. in Computer Science, Electrical Engineering, Biomedical Informatics, or a related field.
• Strong record of research in applied machine learning, NLP, or related AI domains.
• Evidence of peer‑reviewed publications or equivalent research outputs.

Responsibilities

• Lead applied AI/ML research projects in healthcare and biomedical domains.
• Collaborate with clinical investigators and interdisciplinary teams; develop grant proposals and manuscripts.
• Mentor junior data scientists and research staff; guide experimental design and ML methodology.
• Develop and maintain data pipelines, model repositories, and evaluation tools; ensure reproducibility.

Skills

Strong ML research

PyTorch/TensorFlow proficiency

Python programming

Healthcare data experience

Publications evidence

Collaboration skills

Education

Ph.D. in CS/EE/ Biomedical Informatics

Tools

PyTorch

TensorFlow

Job description

University of Illinois Chicago is seeking a Data Scientist to lead and contribute to AI/ML research advancing healthcare delivery and clinical decision-making. The role integrates data science, software engineering, and translational research with a focus on reproducibility and real-world impact.

You will collaborate with faculty, clinicians, and data engineers, mentoring junior researchers and helping build scalable, secure computing environments in alignment with institutional policies.