Overview
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At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we innovate across the full spectrum of healthcare solutions to deliver breakthroughs of tomorrow. Learn more at. We are guided by Our Credo and commit to an inclusive work environment where each person is respected as an individual, with diversity and merit recognized.
Job Function
Data Analytics & Computational Sciences
Job Sub Function
Data Science
Job Category
Scientific/Technology
All Job Posting Locations
Cornellà de Llobregat, Barcelona, Spain, Madrid, Spain
Job Description
Johnson & Johnson Innovative Medicine is seeking a
Senior Scientist
to join the
Data Science & Digital Health (DSDH)
organization, based in Spain. In this role, you will lead the design, execution, and application of advanced computational models to integrate multi‑modal perturbation data and human omics datasets for target/pathway nomination.
Key Responsibilities
You will drive the development of predictive frameworks for disease state reversal, nominate synergistic target combinations, and perform in silico target deconvolution to inform portfolio decisions in immune‑mediated diseases.
In This Role, You Will
Lead the design, optimization, and validation of human‑omics driven perturbation prediction models integrating CRISPR KO, transcriptomics, proteomics, cytokine profiles, and other cellular screening data to predict disease‑reversal phenotypes in disease models.
Develop advanced computational strategies to perform target deconvolution, identify target combinations and pathway perturbation that most effectively reverse pathogenic activity.
Build human‑omics based phenotype scoring frameworks to quantify perturbation efficacy, validated across internal datasets and public databases.
Collaborate closely with therapeutic discovery, disease biology and preclinical safety leads to translate in vitro perturbation outcomes into relevant human disease biology insights, and to translate computational outputs into experimental validation strategies.
Provide technical leadership — set analytical roadmaps, define milestones, quantify success metrics, and ensure reproducibility and scalability across workflows.
Qualifications
Required:
Ph.D. in Bioinformatics, Computational Biology, Data Science, Biomedical Engineering, Computer Science, Artificial Intelligence, or a related field.
2+ years postdoctoral or industry experience in large‑scale multi‑omics data analysis (e.g., genomics, transcriptomics, proteomics), preferably in therapeutic discovery or translational research.
Proven expertise in AI/ML modeling for biological datasets, prediction modeling, phenotype scoring, and multi‑omics integration.
Experience with systems biology/network analysis
Advanced skills in high‑performance/cloud computing, reproducible pipeline development, and workflow optimization.
Excellent written and oral communication skills for multidisciplinary teams. Demonstrated record of impactful research (peer‑reviewed publications, conference talks).
Preferred
Experience in in vitro perturbation data analysis and chemical‑target mapping.
Knowledge of public omics databases.
Background in network/pathway analysis and integrative data harmonization across platforms.
Familiarity with immune‑mediated disease biology, especially fibroblast pathobiology.
Impact of the Role
In this role, you will be at the forefront of J&J’s initiatives to unlock novel therapeutic strategies by integrating proprietary perturbation datasets with cutting‑edge computational modeling. Your work will directly advance therapeutic discovery and translational research. xpzdshu You will have the flexibility to work at our Spanish sites or remotely, with global team integration.
Required Skills
Preferred Skills:
Advanced Analytics
Business Intelligence (BI)
Coaching
Collaborating
Critical Thinking
Data Analysis
Database Management
Data Privacy Standards
Data Reporting
Data Savvy
Data Science
Data Visualization
Econometric Models
Process Improvements
Technical Credibility
Technologically Savvy
Workflow Analysis
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