Principal Data Scientist - San Francisco, United States - Amgen

Amgen

Verified Company

San Francisco, United States

1 week ago

Posted by:

Mark Lane

beBee recruiter

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

Live:

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 multidimensional studies using bulk, singlecell, 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 omicsbased biomarker detection
Collaborate with engineers, data scientists, and research scientists to develop innovative bioinformatics tools and cloudnative workflows that facilitate data access, model utilization, and output interpretation
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 datadriven recommendations to collaborators and crossfunctional partners
Monitor, review, and critically interpret published computational research in the field of computational biology and bioinformatics

Win:

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 singlecell 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/MLOps and software best practices, such as version control, continuous integration, test driven development
Experienced in cloud computing
Creative and openminded, with a passion for scientific research
Exceptional analytical skills, capable of collecting, organizing, analyzing, and disseminating significant amounts of information with attention to detail and accuracy
Demonstrated ability to thrive in a team environment
Strong interpersonal, c