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.

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

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Generative AIAgentic AItranslational sciencemulti-modal data integrationbiomarker analysisprogramming in Rprogramming in Pythonstatistical analysisAI system evaluationhypothesis generation

Soft Skills

scientific leadershipcommunication skillsself-motivationindependencecollaborationinnovationinterpretabilityproblem-solvingcontextualizationstakeholder engagement

Certifications

PhD in BioinformaticsPhD in MathematicsPhD in StatisticsPhD in Computer SciencePhD in Computational BiologyPhD in Data Science