Principal Scientist, Computational Biology-Oncology Translational Research (AI)

Location: Hybrid position based in Spring House, Pennsylvania; Cambridge, Massachusetts; or La Jolla, California, United States

Salary: $115,000–$227,000 base pay annually

Company

Johnson & Johnson MedTech develops healthcare solutions and innovative medicines focused on preventing, treating, and curing complex diseases, including oncology therapies.

What you will do

• Develop and execute computational strategies for oncology translational research and clinical biomarker programs.
• Analyze and interpret multimodal data including DNA/RNA sequencing, proteomics, flow cytometry, single-cell, and spatial transcriptomics.
• Design statistical and machine-learning approaches for biomarker and clinical-outcome analyses, accounting for validation, bias, missingness, batch effects, and analytical limitations.
• Integrate molecular, pathological, assay, sample, and clinical data to evaluate biomarker relevance, clinical utility, and evidentiary strength.
• Generate computational evidence for patient selection, enrichment strategies, MRD initiatives, longitudinal monitoring, and clinical-study interpretation.
• Collaborate across Translational Research, Clinical Development, Statistics, Programming, Pathology, Diagnostics, Data Science, Regulatory, and Biomarker Operations while mentoring others and contributing to publications and presentations.

Requirements

• PhD in Bioinformatics, Computational Biology, Biostatistics, Genomics, Data Science, or a related quantitative field, plus at least 3 years of relevant pharmaceutical or biotechnology industry experience.
• Advanced proficiency in R and experience with Python, Linux/Unix, shell scripting, version control, and reproducible analysis of high-throughput sequencing and multimodal omics data.
• Scientific leadership experience in computational oncology, cancer biology, biomarker applications, oncology drug development, and clinical-trial programs.
• Advanced statistical and machine-learning experience, including regression, multivariate analysis, survival analysis, supervised, semi-supervised, unsupervised, and reinforcement learning.
• Working knowledge of IND and NME development and Phase 1–3 oncology trials, including dose escalation, randomization, stratification, endpoints, censoring, longitudinal data, and treatment response.
• Ability to influence cross-functional stakeholders, defend complex analytical recommendations, communicate limitations, mentor colleagues, and demonstrate scientific impact through publications and presentations.

Nice to have

• Knowledge of CDISC SDTM and ADaM data models, regulatory clinical data management, and biomarker-data traceability.
• Experience with deep learning, multimodal modeling, foundation models, or agentic AI in biomedical research.
• Experience with clinical-trial statistics, including survival and longitudinal models, multiplicity, missingness, treatment-effect heterogeneity, and external validation.
• Experience supporting patient selection, companion or complementary diagnostics, regulatory activities, or biomarker submissions.

Culture & Benefits

• Inclusive work environment guided by the company’s Credo and focused on patient impact.
• Eligibility for a pension and 401(k) savings plan, subject to plan terms.
• Eligibility for the long-term incentive program.
• Paid vacation, sick time, holidays, personal and family time, parental leave, caregiver leave, bereavement leave, volunteer leave, and military spouse time-off.