Principal Data Scientist – Bioinformatics Technologies

Career Category

Job Description

HOW MIGHT YOU DEFY IMAGINATION?

If you feel like you’re part of something bigger, it’s because you are. At Amgen, our shared mission—to serve patients—drives all that we do. It is key to our becoming one of the world’s leading biotechnology companies. We are global collaborators who achieve together—researching, manufacturing, and delivering ever-better products that reach over 10 million patients worldwide. It’s time for a career you can be proud of.

Principal Data Scientist - Bioinformatics Technologies

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What you will do

Let’s do this. Let’s change the world. In this vital role you will join the Bioinformatics Technologies team within Amgen’s Center for Research Acceleration by Digital Innovation (CRADI). CRADI is a multi-disciplinary effort embedded within our drug discovery engine that continually uses advancement in digital technologies for disease modeling and digital modality engineering to accelerate our pipeline from target inception through drug development. This pivotal role within CRADI’s Computational Biology and Bioinformatics platform will assist in establishing an innovation engine for deploying and exploiting emerging digital technologies in the field of computational biology.

In this role you will set strategy, develop, and implement computational models on multi-modal, multi-omics data to accelerate the execution of strategic imperatives for preclinical biomarker discovery. Work collaboratively with scientists within preclinical research and clinical biomarkers as well as data scientists and engineering partners across Amgen R&D. An ability to communicate clearly and collaborate effectively with colleagues from different fields will be essential.

• Design, execute, interpret, and report on multi-dimensional studies using bulk, single-cell, and spatial omics technologies that will expedite the pace of research biomarker discovery and translation in early drug discovery across therapeutic areas

• Find opportunities and set strategy for digital innovation in the field of computational biology

• Initiate and lead the development of advanced quantitative methods, such as topological data analysis, causal inference, discriminative, and generative AI/ML, to push the state of the art in integrative omics-based biomarker detection

• Collaborate with engineers, data scientists, and research scientists to develop innovative bioinformatics tools and cloud-native workflows that facilitate data access, model utilization, and output interpretation

• Serve as subject matter expert for multi-modal single-cell and spatial omics technologies

• Mentor junior data scientists and engineers, providing technical guidance within a formal or matrix structure

• Advise stakeholders on omics data generation, analysis, and interpretation

• Translate findings into computational model design and refinement

• Document methods and analyses to ensure reproducible research

• Communicate project results and data-driven recommendations to collaborators and cross-functional partners

• Monitor, review, and critically interpret published computational research in the field of computational biology and bioinformatics

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What we expect of you

We are all different, yet we all use our unique contributions to serve patients. The professional we seek is a scientist with these qualifications.

Basic Qualifications:

Doctorate degree

Or

Master’s degree and 6 years of computational biology, bioinformatics, biomedical data science or related field

Or

Bachelor’s degree and 8 years of computational biology, bioinformatics, biomedical data science or related field

Preferred Qualifications:

• PhD in computer science, data science, computational biology or bioinformatics

• Extensive experience and a deep theoretical understanding of statistical modeling, machine learning, deep learning, causal learning, topological data analysis, and other relevant quantitative methods

• Proven record of innovative thinking to propose and champion the development of novel algorithms and AI/ML models that generated interpretable and actionable results for biomarker discovery

• Solid knowledge in molecular biology and genetics

• Comprehensive understanding of drug discovery and development process

• Skilled in integrative analysis of omics data, including single-cell and spatial sequencing data

• Proficient in systems biology, such as in silico modeling of cellular response to drug or genetic perturbations

• Fluency in scientific programming and tool development with R, Python, or equivalents

• Familiarity with Dev/