Biometrician / Statistician

Zoetis

Education
Benefits
Qualifications

The successful candidate will be responsible for providing statistical support to multiple discovery and development projects in Veterinary Medicine Research and Development. He/she will be responsible for identifying and implementing innovative approaches for design and analysis of clinical and laboratory trials, including but not limited to Bayesian and adaptive clinical trials methods. The individual should be able to review statistical literature in these areas for practical implementation in animal health R&D programs. Participation on project teams and serving as a liaison between biometrics and other departmental groups is required. The successful candidate will assist in the training of scientists in experimental design and related topics. Our department is highly collaborative, and colleagues are expected to actively participate in group meetings to ensure that a common approach is taken to handling clinical and laboratory study data. 

Education:

MS in Biostatistics/Statistics or related field with at least 5 years of direct work experience in the pharmaceutical industry

PhD in Biostatistics/Statistics with emphasis on Bayesian methods, preferably with 1-3 years’ experience

Essential Skills and Attributes:

  • Knowledge of data handling and statistical analysis programming in PC-SAS, R and other relevant software
  • Knowledge of experimental design, mixed linear and non-linear model methodologies, and categorical data analysis
  • Bayesian methods, clinical trial design and analysis
  • Excellent oral and written communication and statistical consulting skills
  • Ability to critically review scientific publications and statistical literature and adapt for implementation
  • Highly organized, able to manage multiple simultaneous projects and significant attention to detail
  • Works well in a team environment

Desirable Skills and Attributes:

  • Experience with adaptive clinical trial design is highly desirable
  • Data mining and machine learning experience is a plus
  • Experience with clinical and laboratory trials for pharmaceutical and/or vaccine products

Full time

Regular

Colleague

Zoetis is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status or any other protected classification. Disabled individuals are given an equal opportunity to use our online application system. We offer reasonable accommodations as an alternative if requested by an individual with a disability. Please contact Zoetis Colleague Services at zoetiscolleagueservices@zoetis.com to request an accommodation. Zoetis also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as employment eligibility verification requirements of the Immigration and Nationality Act. All applicants must possess or obtain authorization to work in the US for Zoetis. Zoetis retains sole and exclusive discretion to pursue sponsorship for the acquisition or maintenance of nonimmigrant status and employment eligibility, considering factors such as availability of qualified US workers. Individuals requiring sponsorship must disclose this fact. Please note that Zoetis seeks information related to job applications from candidates for jobs in the U.S. solely via the following: (1) our company website at www.Zoetis.com/careers site, or (2) via email to/from addresses using only the Zoetis domain of “@zoetis.com”. In addition, Zoetis does not use Google Hangout for any recruitment related activities. Any solicitation or request for information related to job applications with Zoetis via any other means and/or utilizing email addresses with any other domain should be disregarded. In addition, Zoetis will never ask candidates to make any type of personal financial investment related to gaining employment with Zoetis.

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Confirmed 5 hours ago. Posted 30+ days ago.

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