Data Scientist (USA)
Imagene AI
The role
Job description
Description
We’re looking for a Data Scientist to join our growing team and help develop AI solutions at the intersection of oncology, precision medicine, and drug development.
In this role, you will work closely with data scientists, engineers, scientists, and product to turn complex biomedical data into meaningful AI-driven workflows. You will contribute to research, experimentation, and model development across digital pathology, clinical data, and LLM-based applications.
This is a great opportunity for someone who wants to grow in a highly interdisciplinary environment, learn from an experienced team, and take part in building technology that can support the future of precision oncology.
Responsibilities
- Develop and evaluate ML, deep learning, and LLM-based workflows for digital pathology and oncology data.
- Build data and model pipelines for biopsy images, clinical records, reports, and other biomedical datasets.
- Use LLM tools and coding assistants to accelerate research, analysis, prototyping, and workflow automation.
- Design and run experiments, analyze model performance, and translate results into clear conclusions.
- Collaborate with data scientists, engineers, pathologists, and clinical experts to turn research questions into working AI solutions.
Requirements
- BSc or MSc in Software Engineering, Computer Science, or a related field
- 5+ years of experience in deep learning and machine learning algorithm development.
- 3+ years of experience developing instance segmentation models.
- 2+ years of experience working with LLMs and prompt engineering.
- Experience using AI coding tools such as Cursor, Claude Code, or similar tools.
- Strong analytical skills, attention to detail, and ability to learn quickly.
Position terms:
- Location: Remote (in the USA)
Originally posted on Himalayas
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Listing details
- Listed location
- United States
- Employment
- Full Time
- Published
- Jun 21, 2026
Listing trust
- Observed through
- Himalayas
- Listing last observed
- Jul 27, 2026
Work-from eligibility is based on normalized evidence in the listing: United States.
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