Principal Scientist, Computational Biology Oncology
- 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. 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.
- 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.
- 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.
YOUR APPLICATION
Bayer offers a wide variety of competitive compensation and benefits programs. If you meet the requirements of this unique opportunity, and want to impact our mission Health for all, Hunger for none, we encourage you to apply now. Be part of something bigger. Be you. Be Bayer.
To all recruitment agencies: Bayer does not accept unsolicited third party resumes.
Bayer is an Equal Opportunity Employer/Disabled/Veterans
Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodation(s) using the contact information below.
Equal Opportunity Employer Statement: Notice for U.S. Visitors: All information on this site is subject to compliance with local rule and regulations as they may vary from time to time and across different geographies, including, without limitation, U.S. Executive Orders. Bayer is an E-Verify Employer. Location: United States : Massachusetts : Cambridge Division: Pharmaceuticals Reference Code: 868028 Contact Us Email: [email protected]
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