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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 and Johnson Innovative Medicine (JJIM) is seeking a highly accomplished Senior Scientist to develop and apply multiomics integration methods and frameworks for biomarker identification and patient subtyping, with the goal of enabling precision medicine strategies across disease areas and across discovery and clinical development.

 

This role will focus on extracting, quantifying, and translating complex multimodal biological data into actionable insights that inform patient stratification, biomarker strategy, and target–biomarker–disease understanding. The successful candidate will operate at the intersection of computational biology, translational science, and therapeutic area (TA) collaboration. This is an onsite role based in Spain, with Madrid as the primary location and Barcelona as a secondary option. Hybrid and fully remote arrangements may be considered on a case-by-case basis.

 

Key Responsibilities

• Develop, implement, and apply integrative multiomics frameworks to identify biomarkers and patient subtypes relevant to xTA discovery and clinical precision strategies.

• Integrate diverse data modalities, including genomics, transcriptomics, proteomics, single-cell/spatial omics, QTLs, imaging, and clinical/real-world data, to characterize disease heterogeneity.

• Design patient stratification and subtyping approaches that link molecular signatures to disease mechanisms, prognosis, and treatment response.

• Quantify and prioritize biomarker evidence supporting target engagement, pharmacodynamic response, and patient selection.

• Apply systems biology, network analysis, and statistical/ML methods to connect targets, pathways, biomarkers, and clinical phenotypes.

• Partner closely with discovery, translational, and clinical teams to ensure biomarker and subtyping outputs directly support decision making.

• Contribute to the definition of best practices, reusable pipelines, and scalable platforms for multiomics biomarker discovery.

• Clearly communicate complex analytical results to scientific and clinical stakeholders through compelling narratives, visualizations, and presentations.

 

 

Required Qualifications

• PhD in Computational Biology, Bioinformatics, Systems Biology, Genetics, Biostatistics, or a related quantitative life science discipline, with relevant postdoctoral or industry experience.

• Strong hands-on experience in multiomics data integration and analysis, particularly in the context of human disease.

• Demonstrated expertise in biomarker discovery, patient stratification, or translational data science.

• Solid understanding of human genetics, functional genomics, and molecular disease mechanisms.

• Proficiency in programming and data analysis (e.g., R, Python) and working with large-scale biological datasets.

• Proven ability to work effectively in cross functional, matrixed research environments.

 

Preferred Qualifications

• Experience supporting precision medicine or clinical development programs through biomarker or subtyping strategies.

• Familiarity with proteomics, single-cell and spatial omics and their application to patient heterogeneity.

• Exposure to AI/ML approaches for biomarker discovery or patient stratification.

• Prior experience collaborating directly with clinical, translational, or regulatory stakeholders.

• Track record of high impact publications, platform development, or internal scientific influence.

 

Impact of the Role

This role will directly shape how multiomics evidence is leveraged to define patient populations, guide biomarker strategy, and enable precision medicine, influencing both near-term program decisions and long-term platform capabilities.

 

 

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