Principal Scientist, Manufacturing Statistics

Johnson & Johnson

Principal Statistician leading statistical modeling efforts in manufacturing at Johnson & Johnson. Collaborating with chemists and engineers to support pharmaceutical research and development.

Posted 5/29/2026full-timeBeerse • 🇧🇪 BelgiumLeadWebsite

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

statistical modelingsolubility modelingBayesian Optimizationdesign of experimentschemometric analysisspectral analysisprogramming in Rprogramming in Pythondata analysismechanistic modeling

Soft Skills

clear communicationrelationship buildingmentorshipcross-functional collaborationtrust buildingpresentation skillsstatistical guidancetraininginterpretation of evidenceadvocacy for reproducible code

Tools & Technologies

ssNMRTHz-RamanXRDstatistical softwaredata governance toolsdocumentation toolsexperimental design toolsdata analysis toolsworkflow management systemscollaboration platforms

Certifications & Qualifications

Ph.D. in StatisticsM.S. in StatisticsBiostatistics certificationChemometrics certification

Industry Keywords

pharmaceuticalbiotechchemical processreproducible workflowsbest practicesproduct commercializationstatistical trainingevidence-based researchoutlier detectionshelf-life estimation

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Lead statistical strategy and execution for projects including solubility modeling and prediction; accelerated stability and shelf-life estimation; reaction trend fingerprinting and outlier detection; dissolution modeling; mechanistic modeling; and spectral analytics (ssNMR, THz-Raman, XRD)
Develop design of experiments and Bayesian Optimization workflows to accelerate method development and reaction optimization
Lead chemometric and spectral analysis pipelines
Work closely with researchers on experimental design, data analysis, interpretation, and clear communication of evidence to support research, development, and product commercialization
Co-author scientific publications and present research findings at internal and external forums
Build and maintain trusted relationships with colleagues and stakeholders through clear, reliable statistical guidance
Support internal capability building through statistical trainings, mentorship, and the development and dissemination of best practices and reproducible workflows

Requirements

What you’ll need

Advanced degree in Statistics, Biostatistics, Chemometrics or a closely related discipline (Ph.D. preferred; M.S. considered with exceptional experience)
Minimum 5 years of applied statistical modeling experience in pharmaceutical, biotech, or chemical process environments or equivalent industry experience
Strong expertise in Bayesian and frequentist methods, including experience with design of experiments
Hands-on programming proficiency in R and/or Python
Demonstrated ability to lead cross-functional collaborations and to present complex statistical concepts clearly to non-statistical audiences
Advocate of reproducible code, robust documentation, and sound data governance practices
Strong communicator capable of building trust across scientific, engineering and product teams.

Benefits

Comp & perks

Health care services
On-site sport accommodations
Meal vouchers
Competitive renumeration package
Continuous training
Support and career development programs