ROLE SUMMARY

At Pfizer, we are developing and applying state-of-the-art computational and systematic approaches to better understand disease biology and drive drug discovery. Pfizer Oncology Computational Biology group is seeking a highly skilled and motivated bioinformatician to join a dynamic and innovative team that develops data and AI/ML solutions for oncology research and development. The successful candidate will play a key role in our discovery & translational research efforts, focusing on multi-omics data analysis and developing AI/ML models for predicting drug response and deriving novel biological and therapeutic insights. This is an exciting opportunity to make an impact at all stages of cancer drug discovery including target identification, translational research, and precision medicine in a collaborative and inter-disciplinary environment.

• Multi-omics data analysis: Utilize advanced computational techniques to analyze diverse types of omics data, including single-cell genomics and spatial transcriptomics. Apply statistical and bioinformatics methods to extract meaningful insights from data.
• AI/ML model development: Design and implement state-of-the-art machine learning and deep learning models to predict therapeutic outcome, investigate biological mechanisms and identify novel therapeutic hypotheses. Develop innovative approaches to improve model performance and interpretability.
• Data integration and visualization: Integrate and analyze diverse large-scale datasets from the in vitro, in vivo and clinical settings. Develop data visualization tools and platforms to enable data access, exploration, interpretation.
• Discovery and translational research: Collaborate with cross-functional teams of experimental and computational biologists to support technology development and perform analyses to address questions arising from drug development. Translate data and AI/ML derived hypotheses into actionable recommendations for target discovery, biomarker identification and personalized medicine.

• PhD in computational biology, bioinformatics or a closely related field with
• Relevant working experience in biopharmaceutical industry or academia.
• Strong expertise in multi-omics data analysis, including genomics, transcriptomics, single-cell and spatial transcriptomics. Proficiency in relevant tools and software packages (e.g., R/Bioconductor, Python, MATLAB) is required.
• Demonstrated experience in developing and implementing AI/ML models for biomedical applications. Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch) is highly desirable.
• Programming and scripting skills in languages such as Python, R, or MATLAB.

• Solid understanding of statistical methods and their application to biological data analysis.
• Experience with statistical modeling, hypothesis testing, and data visualization.
• Excellent problem-solving and analytical skills, with a proven ability to work independently and as part of a team.
• Effective communication skills, both written and verbal, with the ability to present complex scientific concepts to diverse audiences.
• Strong publication record in peer-reviewed journals and demonstrated ability to contribute to scientific research.
• Knowledge and experience with cancer biology and/or drug discovery.