Bristol-Myers Squibb Company

Principal Scientist

New Brunswick, NJ, United States
Apr 12, 2019
Required Education
Position Type
Full time
Bristol-Myers Squibb is seeking an experienced Statistician to join the Engineering Technologies group within the Drug Product Science and Technology department. Are you looking for a patient-centric company that will inspire you and support your career? Then join our diverse and innovative team, where we provide rigorous numerical, statistical and data science solutions to a wide array of assignments, ranging from pre-clinical to commercial manufacturing support.


Uses knowledge and expertise of statistics to collaborate with scientists in the design experiments for: formulation development and optimization, process design and optimization, experimental manufacturing campaigns, determining manufacturing design spaces, validation of new assays, and experimental and registrational stability studies. The successful candidate contributes to the CMC development of biological and oral solid drug products.

Analyzes experimental data to support the development of product specifications and regulatory filings.

Engages and leads scientific and technical discussions with multi-disciplinary team members to move forward with speed and accountability.

Clearly communicates and documents results to stakeholders with diverse backgrounds, including non-technical audiences.

Develops visualization techniques to facilitate interpretation of experimental data and models by non-statisticians. Trains scientists in data analysis, statistics, and visualization.

Applies regulatory guidelines to work and keeps abreast of technical and regulatory advancements. Authors source documents used in CMC registrational filings. Assists in developing responses to health agencies.

Participates in functional and cross-functional initiatives, including process and quality improvements.


PhD or MS in Statistics, Biostatistics, or a related field, with a minimum of 7 years of relevant industry experience. Candidates with documented equivalent experience in an applied statistical setting will be considered.

Pharmaceutical development experience and knowledge of CMC is desired. Expertise in other scientific/engineering/computing areas is a plus.

Advanced knowledge of DoE, multivariate statistics, general linear models and mixed models is essential. Reliability statistics knowledge is a plus.

Candidate must be proficient with SAS. Experience with R or S-Plus, and/or JMP is desired.

Understanding of regulatory guidelines (e.g. cGMP and ICH guidance) that impact the use of statistical analysis for setting specifications and predicting shelf life is preferred.

A successful candidate will have excellent computational, written and verbal communication skills, strong organizational abilities and an ability to work with a diverse group of scientists and engineers.