Senior Data Science & Biomarker Leader

Bristol-Myers Squibb Co; United States; On-site; USD 148,000 - 207,000; Full time

Benefits offered by this job

Health Coverage

Wellbeing Programs

401(k) Plan

Paid time off

Job summary

Bristol Myers Squibb is seeking a Senior Manager, Data Scientist to advance drug development through cutting-edge data science. You will translate multimodal data into testable hypotheses, develop predictive biomarkers, and drive analytics strategies across clinical programs.

The role requires deep expertise in AI/ML, omics data analysis, and collaboration with clinicians, statisticians, and IT to enable biomarker-driven decision making in a fast-paced environment.

Qualifications

• Ph.D. in Computational Biology, Biostatistics, Statistics, Computer Science or related field with 1+ year industry experience or Master’s with 3+ years industry experience.
• Strong experience analyzing omics or molecular assay data.
• Experience in pharma R&D and AI/ML applications.
• Proficiency in SQL, Python, R and cloud platforms.
• Excellent communication and collaboration skills.

Responsibilities

• Develop computational methods for patient segmentation from multimodal clinical/omics data.
• Collaborate on protocols and SAPs for biomarkers and diagnostics in drug development.
• Analyze biomarker data from trials and real-world cohorts.
• Develop and validate predictive models and apply state-of-the-art algorithms.
• Lead cross-functional teams and coordinate resources to deliver results on time.

Skills

AI/ML experience

SQL

Python

R

Cloud platforms

Statistical modeling

Data analysis

Cross-functional collaboration

Communication

Education

Ph.D. or M.S. with industry experience

Tools

Cloud platforms

Job description

Bristol Myers Squibb is seeking a Senior Manager, Data Scientist to advance drug development through cutting-edge data science. You will translate multimodal data into testable hypotheses, develop predictive biomarkers, and drive analytics strategies across clinical programs.

The role requires deep expertise in AI/ML, omics data analysis, and collaboration with clinicians, statisticians, and IT to enable biomarker-driven decision making in a fast-paced environment.