Application link: https://pfizer.wd1.myworkdayjobs.com/PfizerCareers/job/United-States---Massachusetts---Cambridge/Senior-Scientist---Computational-Biologist_4909646-2

Job Summary: The Senior Scientist Computational Biologist will be a key member of the Machine Learning and Computational Sciences Team, focusing on the analysis and interpretation of complex datasets generated from omics experiments to drive drug discovery and development. The role will require applying a deep understanding of biology together with advanced computational methods to solve complex biological problems and contribute to the understanding of disease mechanisms at the molecular level. The successful candidate will demonstrate an enthusiasm to work, collaborate, and communicate with both computational and experimental colleagues.

Key Responsibilities:
Develop and apply computational tools and algorithms for the analysis of large-scale proteomics datasets.
Collaborate with cross-functional teams to design, guide, conduct statistical analysis, and interpret multi-omics datasets including proteomics, NGS, and chemical biology data in the context of drug discovery projects.
Contribute to the development of machine learning models for predicting protein function and interactions.
Stay abreast of the latest developments in proteomics and computational biology. Integrate new technologies and methodologies into research practices.
Communicate findings effectively to both technical and non-technical audiences through presentations and scientific publications.

Qualifications:
Ph.D. in computational biology, bioinformatics, statistics, computer science, or a related technical field.
Strong background in omics type data analysis and interpretation, such as proteomics, metabolomics, genomics, transcriptomics, etc.
Proficiency in programming languages such as Python or R and experience with bioinformatics tools and databases.
Deep understanding of biological systems, including post-translational modification, molecular and cell biology, pathway regulation, etc.
Familiarity with machine learning techniques and their application to biological data.
Experience with mass spectrometry-based proteomics/metabolomics, chemical biology, Olink proteomics, and next-generation sequencing is preferred.
Excellent problem-solving skills and the ability to work independently and as part of a team.
Strong communication skills and a track record of scientific publications in peer-reviewed journals.

Candidate demonstrates a breadth of diverse leadership experiences and capabilities including: the ability to influence and collaborate with peers, develop and coach others, oversee and guide the work of other colleagues to achieve meaningful outcomes and create business impact.
Relocation support available

Work Location Assignment: Cambridge, MA, USA On Premise/Hybrid