Senior Director, Integrative Biology- Oncology Discovery

Johnson & Johnson•Spring House, PA

5d•Onsite

About The Position

Johnson & Johnson is seeking a visionary Senior Director to lead the Oncology Integrative Biology team and provide scientific and strategic leadership for computational biology within Oncology Discovery across disease areas. Oncology Integrative Biology is a cross-disease-area team integrating biological evidence and emerging computational approaches to advance target identification and validation, generate precision medicine hypotheses, and deepen pathway biology across pre-portfolio and portfolio programs. The team will pioneer AI-enabled discovery biology in close partnership with disease-area teams, DPDS, Data Science, Translational Oncology, and other discovery partners. As a member of the Discovery Senior Leadership Team, the Senior Director will serve as a scientific partner to Oncology Discovery leaders, DASL, Translational Research, and discovery project teams. The role uses large-scale biological datasets to generate actionable insights and inform drug discovery strategy. The leader will build and develop a high-performing computational biology capability, establish fit-for-purpose computational strategies across the discovery portfolio, and ensure computational insights are translated into clear biological hypotheses and decisions. The integrative discovery team is expected to grow to up to 10 FTE over the next several years. The leader will also implement and drive AI Native-related workstreams supporting the Oncology Discovery team.

Requirements

Ph.D. or equivalent advanced degree in Computational Biology, Bioinformatics, Systems Biology, Genetics/Genomics, Biostatistics, Data Science, or a related discipline.
Deep expertise in cancer biology and oncology drug discovery.
12+ years of relevant industry experience.
Significant computational biology leadership experience, with a track record of scientific impact, team development, and influence across multidisciplinary discovery teams.
Demonstrated expertise applying statistical and computational methods to complex genomics and multi-omics data.
Ability to translate computational results into testable biological hypotheses and clear recommendations for experimental scientists and senior decision-makers.

Nice To Haves

Big Data Management
Data Reporting
Developing Others
Drug Discovery Development
Inclusive Leadership
Leadership
Molecular Diagnostics
Pharmaceutical Microbiology
Product Knowledge
Project Reporting
Regulatory Affairs Management
Risk Management
Scientific Research
Stakeholder Engagement
Standard Operating Procedure (SOP)
Strategic Thinking
Sustainability

Responsibilities

Define and execute the computational biology strategy for Oncology Discovery, aligned with therapeutic-area priorities and portfolio needs across multiple therapeutic modalities.
Lead computational approaches for target identification and validation, disease segmentation, mechanism-of-action understanding, and biomarker hypotheses to inform therapeutic opportunities.
Integrate human tumor, patient-derived, multi-omics, and functional genomics data to generate mechanistic insights and experimentally testable hypotheses in cancer biology.
Advance the application of machine learning, AI, network biology, predictive modeling, and multimodal data integration to oncology discovery questions.
Partner with data science, AI/ML, informatics, and technology teams to develop scalable analytical approaches and evaluate emerging methods and platforms.
Champion rigorous, reproducible, and interpretable computational science, ensuring analyses lead to biologically meaningful and experimentally testable hypotheses.
Embed computational thinking and AI early in discovery programs, partnering with project teams to translate biological questions and quantitative insights into experimental and portfolio decisions.
Establish evidence frameworks for evaluating targets and therapeutic hypotheses, drawing on insights across programs and datasets.
Communicate complex computational findings in clear biological and strategic terms to Discovery teams and senior leadership.
Recruit, lead, mentor, and develop computational biologists, fostering scientific excellence, innovation, collaboration, and deep understanding of cancer biology.
Establish priorities and deploy computational resources against high-impact scientific questions.
Build productive partnerships across Oncology Discovery, Translational Research, Data Science, AI/ML, Precision Medicine, and other R&D functions.
Maintain awareness of emerging advances in cancer genomics, functional genomics, single-cell and spatial biology, computational biology, AI/ML, and drug discovery.
Establish collaborations with academic investigators, biotechnology companies, technology providers, and other external partners.
Represent the organization at scientific conferences and through publications and other external scientific interactions.
Implement and drive AI Native-related workstreams to support the Oncology Discovery team.