Sr. Principal Scientist (Translational Safety)

Role Summary

Sr. Principal Scientist (Translational Safety) — Lead scientific direction in Translational Safety and Risk Sciences, applying AI/ML and computational biology to analyze multi-modal omics, nonclinical, and clinical data to identify safety signals and translational insights across drug development from late-stage discovery to marketed products. Collaborate across teams within Amgen and mentor staff to accelerate the development of safe and effective therapies.

Responsibilities

• Identify and evaluate putative safety signals, mechanistic liabilities, translational risk patterns/phenotypes and pathway mechanisms by applying computational biology approaches that leverage ML/AI methods, data integration, multimodal omics data, and biological knowledge across multiple therapeutic areas.
• Collaboratively develop automated data aggregation, processing, visualization, and interpretation pipelines.
• Comfortably navigate a highly matrixed environment and collaborate internally with colleagues within Amgen such as TSRS, the Center for Research Acceleration through Digital Innovation (CRADI), R&D AI Strategy & Execution (RAISE), Digital Technology and Innovation (DTI), and subject matter expert teams to align AI/ML initiatives with overall strategic project goals of the TSRS organization and drive impactful decision-making.
• Champion innovation by tapping into expertise in ML/AI, data science, and advanced modeling to propose new technical strategies that address the business challenges.
• Contribute to regulatory documentation by generating mechanistic off target insights into safety hazards/risks and predictive safety assessments
• Lead evaluations of novel computational methods, tools, and software for applicability in nonclinical safety.
• Provide expertise and mentorship in computational biology, data science methodologies, and ML/AI algorithms development to Amgen colleagues.
• Exemplify a self-starter mentality towards continuous learning and broadening impact. Continue to develop scientific expertise, credentials, and drug development expertise by keeping abreast of relevant literature and by expanding scientific/technical knowledge.

Qualifications

• Required: Doctorate degree PhD OR PharmD OR MD [and relevant post-doc where applicable] in Computational Biology, Bioinformatics, Computer/Data Sciences, Life Sciences or a related field and 3 years of pharmaceutical/biotechnology industry experience applying computational methods to support drug discovery/development
• Required: Or Master’s degree in Computational Biology, Bioinformatics, Computer/Data Sciences, Life Sciences or a related field and 6 years of pharmaceutical/biotechnology industry experience applying computational methods to support drug discovery/development
• Required: Or Bachelor’s degree in Computational Biology, Bioinformatics, Computer/Data Sciences, Life Sciences or a related field and 8 years of pharmaceutical/biotechnology industry experience applying computational methods to support drug discovery/development
• Preferred: 5 years post-PhD or 10 years post-Master’s degree of pharmaceutical/biotechnology industry experience applying computational methods to support drug discovery/development
• Preferred: Reputation as an emerging leader in the field with a proven track record of drug discovery project leadership in a biotechnology or pharmaceutical environment
• Preferred: Ability to analyze and interpret large scale datasets with proficiency in programming tools such as Python, R, shell scripting, SQL or other languages
• Preferred: Proficiency in data visualization and dashboarding frameworks (e.g., Spotfire, Tableau, R, R-Shiny)
• Preferred: Ability to design workflows and data analysis pipelines for automated and standardized analysis of large data sets
• Preferred: Demonstrated experience with advanced AI/ML techniques and statistical modeling (e.g., multivariate linear regression, cluster algorithms, logistic regression, Neural Networks, etc.)
• Preferred: Understanding and preferably hands-on experience with cloud platforms such as Azure and AWS
• Preferred: Excellent interpersonal skills with the ability to build strong collaborations across matrixed teams.
• Preferred: Excellent communications skills with an ability to clearly articulate complex scientific concepts to both technical and non-technical partners.
• Preferred: A strong teammate and scientific leader with a passion for science and drug discovery
• Preferred: Positive attitude and high personal and ethical standards
• Preferred: Fundamental understanding of biopharmaceutical research, drug development pipelines, toxicology data generation, and a working understanding of innovative science and technology being used to enhance investigation of drug development safety issues.