Senior Scientist Discovery Statistics

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 are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at https://www.jnj.com

Job Function:

Data Analytics & Computational Sciences

Job Sub Function:

Biostatistics

Job Category:

Scientific/Technology

All Job Posting Locations:

Cambridge, Massachusetts, United States of America, Raritan, New Jersey, United States of America, 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

Johnson & Johnson Innovative Medicine (JJIM) Research & Development, L.L.C., is recruiting a Senior Statistician to join the Discovery Unit within the Discovery and Manufacturing Statistics (DMS) group to be located at Cambridge, MA, Raritan, NJ, Titusville, NJ, or Spring House, PA.

The Discovery group within the DMS department, part of the Statistics and Decision Sciences organization at J&J, is committed to strategic and statistical leadership in the learning phase of drug discovery research and development.   It provides statistical expertise in preclinical research and integrates this information toward optimal designs for early development trials and provides a platform for synthesizing quantitiative information on compounds and disease areas to facilitate dose/regimen selection, patient enrichment and Go/no-go decision making.  It is committed to the delivery of high-quality data analytic and data science solutions for all Therapeutic Areas (TAs) Janssen R&D is committed to.  DMS represents a global team of statisticians located in Beerse (Belgium), Leiden (The Netherlands), Prague (Czechia), High Wycombe (UK), Spring House (PA, USA), Raritan (NJ, USA) and La Jolla, (CA, USA) campuses.

Job Description

The successful candidate will contribute to statistical services in support of discovery programs for all therapeutic areas and modalities (small molecules, biologics and advanced therapies).  He/she will contribute to making informed decisions in discovery through his/her analytical mindset, analysis skills, experimental design suggestions and through appropriate reporting and communication of data evidence.  The candidate will collaborate with cross-functional teams and with external contractors. 

Key responsibilities of the position include:

• Engage in collaborative efforts with researchers on experimental design, data analysis, interpretation, and clear communication of evidence to support research, development, and product commercialization within JJIM Research & Development or related Johnson & Johnson divisions.

• Ensure the appropriate application of statistical methodologies tailored to each research need.

• Contribute as a co-author to scientific publications and presentations presenting research findings.

Skills and Knowledge:

• Excellent oral and written communication skills are essential, along with a strong motivation to acquire sufficient knowledge of relevant sciences to engage effectively.

• Solid understanding of biostatistics is essential to this role, along with a keen interest in expanding your grasp of underlying sciences and business contexts.

• Proficiency in R and its ecosystem, including graphic capabilities, data wrangling with tidy data principles, modeling, reporting, and developing reproducible code.

• Deep expertise in omics analyses, experimental design, (non)-linear mixed models, multivariate analysis, Bayesian statistics and/or expertise in modern visualization methods required.

• Passion for adopting modern data analysis techniques, such as AI/ML, Bayesian modeling, data visualization, and high-dimensional data analysis.

• Eagerness to continually enhance expertise in stati