Job Function: Data Analytics & Computational Sciences
Job Sub Function: Biostatistics
Job Category:Scientific/Technology
All Job Posting Locations:Spring House, Pennsylvania, United States of America
Job Description:About Innovative Medicine:Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.
Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.
Learn more at https://www.jnj.com/innovative-medicine
We are searching for the best talent for a Senior Principal Statistician in Spring House, PA.Remote work options may be considered on a case-by-case basis and if approved by the Company.
Please note that this role is also available across multiple countries and may be posted under different requisition numbers to comply with local requirements. While you are welcome to apply to any or all of the postings, we recommend focusing on the specific country(s) that align with your preferred location(s):
Canada - Requisition Number: R-099269
United States - Requisition Number: R-097788
Remember, whether you apply to one or all of these requisition numbers, your applications will be considered as a single submission.
Purpose:We are seeking an outstanding Senior Principal Statistician to join our Discovery Oncology Statistics organization within Johnson & Johnson Innovative Medicine Research & Development. This scientific leadership role provides strategic statistical leadership across oncology drug discovery programs, representing statistics in key scientific and portfolio discussions and helping drive critical decisions from target identification through candidate selection and translational biomarker development.
This is an exciting opportunity to influence the future of cancer drug discovery by applying innovative statistical methodologies, machine learning, data science, and quantitative decision-making to some of the most exciting scientific questions in oncology. The successful candidate will collaborate across multidisciplinary research teams and contribute to innovation that directly impacts the advancement of transformational medicines for patients.
You will be responsible for:- Lead statistical strategy for priority oncology programs and shape scientific and portfolio decisions through quantitative evidence.
- Apply and advance statistical modeling, AI/ML, biomarker analytics, and quantitative decision frameworks to accelerate drug discovery.
- Drive experimental design, modeling, and data analysis across translational, in vivo, combination, and high-dimensional studies.
- Forge partnerships across functions and external organizations to advance program objectives and quantitative decision-making.
- Develop analytics capabilities, AI-enabled workflows, statistical methods, and decision-support tools with data science partners.
- Champion reproducible research, data integrity, statistical standards, and methodological rigor.
- Lead publications, scientific presentations, and external collaborations that advance statistical methods and scientific practice.
Qualifications / Requirements:Education:- Minimum of a PhD in Statistics, Biostatistics, Applied Statistics, Bioinformatics, Data Science, or a related quantitative discipline with a minimum of 6 years of relevant experience in pharmaceutical, biotechnology, or healthcare research is required.
Required: - Recognized expertise in statistical methods, experimental design, and quantitative decision-making for drug discovery and translational research.
- Track record of influencing scientific and portfolio decisions through quantitative evidence.
- Experience applying modeling, simulation, predictive analytics, and high-dimensional data analysis.
- Ability to translate statistical concepts into actionable insights for scientific and business audiences.
- Scientific leadership of complex programs, shaping scientific strategy and decision-making across multidisciplinary teams.
- Proficiency in R and modern computational and AI-enabled workflows.
- Travel: Up to 10-15% domestic and international travel may be required.
Preferred:- Recognized expertise in oncology drug discovery, translational research, and biomarker-driven decision-making.
- Experience applying machine learning, artificial intelligence, and advanced analytical methods to biomedical and drug discovery datasets.
- Experience with genomic, transcriptomic, proteomic, imaging, spatial biology, or other multi-omics datasets.
- Previous people leadership, mentoring, scientific coaching, or matrix leadership experience.
- Experience leading external collaborations, academic partnerships, scientific consortia, or industry working groups, with a demonstrated record of external scientific impact.
#LI-Hybrid
Required Skills: Preferred Skills: 
