Principal Scientist, Computational Biology Oncology · Bayer

Wed, 29 Apr 2026 15:06:05 GMT
Engineering

Bayer · Cambridge · $136,000.00 - $204,000.00

At Bayer, we're seeking an agile innovator to join our team as a Principal Scientist, Computational Biology Oncology. As a key member of our research and development team, you will play a crucial role in evaluating therapeutic hypotheses via integration and quantitative analyses of internal & external multi-omics data sources (DNA, RNA, CRISPR, ChIP-seq, methylation, and proteomics).

We are growing rapidly with an active research and discovery pipeline. You will design, execute, and interpret complex quantitative analyses to address precision drug development criteria. Examples of precision drug development criteria include RAISE dimensions, translational science strategy, proof-of-mechanism, and lifecycle management.

Contribute to Product Team scientific strategy and prosecution of critical path objectives, such as the identification of novel targets, biomarkers, or patient selection hypotheses. These contributions use state-of-the-art computational biology methods to analyze large and complex data sets.

Deliver biological insights on therapeutic assets and disease biology understanding to Product Teams, who apply these insights towards stage-gate decisions, portfolio prioritization, and/or submissions to Health Authorities.

Educate Product Teams on innovations in disease understanding, especially molecular mechanisms of tumor vulnerabilities that may represent unmet medical need.

Develop, evaluate, implement, and apply Best Practices for the execution and validity of quantitative analyses, integration, visualizations, and interpretation of multi-omics data. Demonstrate a growth mindset towards updating Best Practices with the emergence of new experimental or computational technologies.

Build cross-functional relationships to collaboratively partner across Pharma R&D and effectively network within disease understanding and data science communities of experts.

Responsibilities

Evaluate and contextualize the molecular evidence supporting a therapeutic hypothesis with relevant internal and external multi-omics data (DNA, RNA, CRISPR, ChIP-seq, methylation, and proteomics)

Design, execute, and interpret complex quantitative analyses to address precision drug development criteria

Contribute to Product Team scientific strategy and prosecution of critical path objectives

Deliver biological insights on therapeutic assets and disease biology understanding to Product Teams

Educate Product Teams on innovations in disease understanding

Develop, evaluate, implement, and apply Best Practices for the execution and validity of quantitative analyses, integration, visualizations, and interpretation of multi-omics data

Requirements

PhD degree in Life Sciences (Bioinformatics, Computational Biology, Biology, Genetics, Molecular Biology, or other related discipline) with very strong computational focus

Demonstrated experience in statistical analysis of DNA-seq, RNA-seq, proteomics, single-cell, or imaging datasets with proficiency in a programming environment (such as R or Python)

Demonstrated peer-reviewed publications in computational biology

Expert level of proficiency to choose fit-for-purpose quantitative analyses

Demonstrated ability to propose, catalyze, and implement the development of interdisciplinary, systematic solutions that create business value

Evidence of providing tactical and strategic guidance to the pharma portfolio or data science ecosystem

Strong communication competencies, including capability to present even very complex issues clearly and convincingly to project teams or decision bodies

Demonstrates advanced business acumen, people and project leadership competencies, and technical expertise

Can manage a high degree of organizational and technical complexity

Learning agility, highly self-motivated, with an aspiration of continuous improvement of oneself and others

Preferred Qualifications

5+ years industry experience in drug development or biotech role with clear understanding of applying multi-omics data analyses to advance a portfolio of drug discovery or clinical development projects