Principal Scientist, Translational AI & Predictive Sciences

Bristol-Myers Squibb Co; United States; On-site; USD 145,000 - 202,000; Full time

Benefits offered by this job

Comprehensive benefits

Flexible time off

Job summary

Bristol Myers Squibb is seeking a Principal Scientist in Translational Informatics and Predictive Sciences to lead computational strategies for translational studies. You will work with biomarker scientists, clinical teams, and preclinical researchers to uncover insights from complex molecular data and apply AI-driven approaches across modalities.

The role requires deep expertise in high-throughput data, Python/R skills, and a track record of integrating data to inform decision-making in drug

Qualifications

• Experience with high-throughput molecular data (NGS, single-cell, proteomics).
• Proficiency in R and/or Python with AI in research.
• Strong statistics knowledge.
• Growth mindset and continuous learning.
• Strong problem solving and scientific rigor.
• Excellent communication and cross-functional collaboration.

Responsibilities

• Partner with scientists to design computational strategies for translational studies.
• Analyze high-dimensional molecular data to generate mechanistic insights into treatment response.
• Apply ML/AI methods to extract patterns from multi-omics and real-world datasets.
• Provide scientific leadership and mentorship to elevate analytical practices.
• Communicate results clearly to decision-making bodies across R&D.

Skills

Molecular data

R and Python

Statistics

AI in science

Communication

Education

Bachelor's degree or higher

Master's degree

PhD

Tools

R

Python

Job description

Bristol Myers Squibb is seeking a Principal Scientist in Translational Informatics and Predictive Sciences to lead computational strategies for translational studies. You will work with biomarker scientists, clinical teams, and preclinical researchers to uncover insights from complex molecular data and apply AI-driven approaches across modalities.

The role requires deep expertise in high-throughput data, Python/R skills, and a track record of integrating data to inform decision-making in drug