Principal Scientist – Research Computational Biology (ARIA)

Role Summary

Lead computational biology efforts to accelerate identification, prioritization, and validation of therapeutic targets within ARIA. Provide scientific and technical leadership to shape computational biology strategy across multiple discovery programs, influencing target selection, biomarker strategy, and translational hypotheses. Collaborate with cross-functional teams to advance diverse therapeutic programs.

Responsibilities

• Driving extraction of biological insight from complex multi-modal omics and screening data to characterize disease endotypes and mechanisms, identify novel targets and biomarkers, and test therapeutic hypotheses.
• Developing and leveraging methods and platforms to discover, prioritize, and validate targets across diverse diseases and therapeutic modalities.
• Innovative research in close partnership with Amgen therapeutic area scientists, spanning both internal pipeline programs and external partnerships.
• Shaping roadmap priorities with our data science and information systems teams to incorporate tools and analyses developed within ARIA Computational Biology into integrated R&D platforms.

Qualifications

• Required: Doctorate in computational biology, bioinformatics, data science, or a related discipline [and relevant post-doc where applicable] and 2 years of computational biology experience
• Required: Master’s degree and 5 years of computational biology experience
• Required: Bachelor’s degree and 7 years of computational biology experience
• Preferred: Strong research background in cardiometabolic disease and/or immunology, including mechanistic characterization of disease biology using multi-modal single-cell data.
• Preferred: Proven track record of driving programs or platforms that have materially impacted discovery or early development decisions.
• Preferred: Experience mentoring scientists and setting standards for computational best practices within a team
• Preferred: Ability to integrate portfolio-level business context into research strategy
• Preferred: Strong programming skills (Python, R, Linux/Unix), familiarity with cloud computing environments, HPC, and collaborative coding practices (e.g., Git).
• Preferred: Track record of designing and implementing creative and holistic computational strategies to address challenging research questions.
• Preferred: Demonstrated expertise in the analysis and interpretation of single cell omics data.
• Preferred: Excellent presentation and communication skills to convey complex findings to diverse audiences.
• Preferred: Experience leveraging and fine-tuning transcriptional foundation models, LLMs, and biomedical knowledge graphs to further research goals.
• Preferred: Familiarity with public data resources (e.g. DepMap, Human Cell Atlas, TCGA, GTEx, and Tahoe-100M) frequently used to augment analyses of internally generated data.
• Preferred: Experience developing and deploying tools and pipelines to endpoints such as interactive portals (e.g. RShiny, Streamlit), workflow management systems (e.g Nextflow), and agentic frameworks.