Principal Scientist – Computational Biology, Translational AI, Oncology Precision Medicine

Role Overview

• Lead pan-asset forward and reverse translational analyses, integrating preclinical, translational, and clinical data to generate mechanistic insight, biomarker hypotheses, and development-relevant evidence
• Design and deploy Generative AI and Agentic AI systems that support hypothesis generation, evidence synthesis, and cross-modal reasoning across discovery, translation, and clinical development
• Develop multi-agent, tool-using AI workflows that integrate structured and unstructured data (omics, imaging, pathology, clinical data, literature) to accelerate translational insight generation
• Apply modern statistical and AI-enabled approaches to connect molecular mechanisms, biomarkers, and clinical phenotypes, supporting indication strategy, patient stratification concepts, and learning across assets
• Drive reverse translation by systematically linking clinical observations back to molecular and biological hypotheses using multimodal data and AI-assisted reasoning frameworks
• Analyze and integrate multi-modal translational data (e.g., genomics/transcriptomics, proteomics, epigenomics, single-cell, imaging, pathology, clinical endpoints) to support forward and reverse translational learning across oncology assets
• Build and maintain AI-enabled, reproducible translational analysis pipelines, including integration with agentic systems and automated insight-generation workflows
• Partner with biology, assay, pathology, and clinical teams to contextualize and interpret translational signals, rather than owning routine assay delivery
• Represent CfTI in Amgen program and portfolio teams as a translational science and AI thought leader, contributing AI-enabled forward and reverse translational insight across assets
• Communicate results clearly to clinical and scientific stakeholders and contribute to translational and biomarker strategy, regulatory-facing analyses (as needed), and reverse translation learning

Requirements

• Doctorate degree and 2 years of scientific/biopharma experience OR Master’s degree and 5 years of scientific/biopharma experience OR Bachelor’s degree and 7 years of scientific/biopharma industry experience
• PhD in Bioinformatics, Mathematics, Statistics, Computer Science, Computational Biology, Data Science, or related field, with a strong foundation in biology and translational science
• Demonstrated expertise in forward and/or reverse translational science, linking molecular mechanisms, biomarkers, and clinical outcomes across discovery and development
• Hands-on experience developing Generative AI and/or Agentic AI systems applied to scientific reasoning, hypothesis generation, or evidence synthesis
• Experience integrating multi-modal data (omics, imaging, pathology, clinical, text/literature) using AI-enabled or model-based approaches
• Strong understanding of AI system evaluation, interpretability, and scientific reliability in decision-critical environments
• Working knowledge of clinical biomarker platforms and translational readouts, enabling effective collaboration with assay and clinical teams
• Demonstrated experience generating translational and biomarker insights that influenced clinical development decisions (e.g., indication strategy, trial design, stratification, or mechanistic understanding)
• Strong programming experience in R and/or Python, with experience integrating AI/LLM-driven components into reproducible analysis workflows (version control, workflow orchestration, documentation)
• Familiarity with modern data and analytics infrastructure supporting scalable, auditable AI systems in clinical research environments
• Ability to work effectively in a highly matrixed environment and drive scientific and technical innovation collaboratively across functions
• Strong written and oral communication skills, self-motivation, independence, and scientific leadership.

Tech Stack

• Python

Benefits

• A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions
• Group medical, dental and vision coverage
• Life and disability insurance
• Flexible spending accounts
• A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
• Stock-based long-term incentives
• Award-winning time-off plans
• Flexible work models, including remote and hybrid work arrangements, where possible