Senior Scientist, Computational Biology (Oncology Translational Research)

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

Salary: $109,000–$174,800 annual base pay

Company

Johnson & Johnson develops healthcare, Innovative Medicine, and MedTech solutions focused on preventing, treating, and curing complex diseases.

What you will do

• Analyze multimodal oncology biomarker data and clinical outcomes, including DNA/RNA sequencing, flow cytometry, proteomics, single-cell, and spatial transcriptomics data.
• Integrate molecular, pathological, and clinical data to identify, validate, and evaluate pharmacodynamic, prognostic, predictive, and resistance biomarkers.
• Apply statistical, machine-learning, and AI-enabled bioinformatics approaches to support translational strategies and oncology clinical development.
• Use approved AI-enabled tools for analysis, coding, testing, and documentation while maintaining review, validation, traceability, and reproducibility.
• Collaborate with translational research, clinical development, statistics, programming, pathology, diagnostics, data science, regulatory, and biomarker operations functions.
• Communicate findings and limitations and contribute to scientific publications, presentations, and evaluation of emerging computational and biomarker technologies.

Requirements

• PhD in Bioinformatics, Computational Biology, Biostatistics, Genomics, Data Science, or a related quantitative field, plus 1–3 years of relevant pharmaceutical or biotechnology industry experience.
• Advanced R proficiency and experience with Python, Linux/Unix, shell scripting, version control, and reproducible high-throughput sequencing and multimodal omics analysis.
• Oncology translational or clinical-development experience with knowledge of cancer biology, biomarker applications, and clinical-trial concepts.
• Strong statistical and machine-learning experience, including regression, multivariate analysis, survival analysis, supervised, semi-supervised, unsupervised, and reinforcement learning.
• Ability to independently own biomarker-analysis workstreams, communicate complex analyses and limitations, and collaborate across functions.
• Peer-reviewed publications and scientific presentations demonstrating scientific accomplishments.

Nice to have

• Familiarity with CDISC SDTM and ADaM, regulatory clinical data management, and biomarker-data traceability.
• Experience with deep learning, multimodal modeling, foundation models, or agentic AI in biomedical research.
• Knowledge of IND and NME development, Phase 1–3 trials, clinical endpoints, longitudinal analysis, and time-to-event analysis.
• Experience with patient selection, companion or complementary diagnostics, regulatory, or submission-related biomarker activities.

Culture & Benefits

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