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Associate Director Translational Epidemiology

Posted on Apr 5, 2021 by Bristol-Myers Squibb

Summit, NJ 07902
Research
Immediate Start
Annual Salary
Full-Time


Job Description
At Bristol Myers Squibb, we are inspired by a single vision - transforming patients' lives through science. In oncology, hematology, immunology and cardiovascular disease - and one of the most diverse and promising pipelines in the industry - each of our passionate colleagues contribute to innovations that drive meaningful change. We bring a human touch to every treatment we pioneer. Join us and make a difference.


About Bristol-Myers Squibb


Bristol-Myers Squibb is a global Biopharma company committed to a single mission: to discover, develop, and deliver innovative medicines focused on helping millions of patients around the world in disease areas such as oncology, cardiovascular, immunoscience and fibrosis.


Join us and make a difference. We hire the best people and provide them with a work environment that places a premium on diversity, integrity, collaboration and personal development. Through a culture of inclusion, we create a better, more productive work environment. We believe that the diverse experiences and perspectives of all our employees help to drive innovation and transformative business results.


Position summary:


The Associate Director is a key member of IPS' Translational Epidemiology team and conducts high-quality statistical analyses utilizing real world evidence (RWE) and omics data sources to support research goals, publication plans and cross-functional internal and external collaborations.


The ideal candidate will be a hands-on quantitative epidemiologist, statistician, computational biologist or applied mathematician with experience in large-scale healthcare data processing and analysis. S/he will have experience working with a variety of data sources, such as clinical trial data, electronic health record data, insurance claims data, biobank data, research consortium data, and/or omics data. The candidate must also have a demonstrated ability to actively listen, integrate input from diverse sources, and collaboratively translate medical or business questions into data and analysis requirements and a clear path forward.


Overall responsibilities include:


Represent the Translational Epidemiology group and its capabilities in meetings with nontechnical peers
Work in a fast-paced multidisciplinary dynamic environment, and as necessary create examples, prototypes, demonstrations to help the business better understand innovative solutions
Collaborate with team members to meet project checkpoints and accomplish team objectives
Key competencies, skills, and attributes:


Advanced knowledge of a subset of analytical approaches (ex. statistics, predictive modeling, visual analytics) and the desire to continually learn and grow your analytical skillset
Ability to work with structured and unstructured data
Ability to multi-task and handle numerous complex relationships at a time
Demonstrated ability to engage in effective joint problem-solving to address key challenges
Education and Experience Guidelines:


Preferred advanced degree in Epidemiology, Biostatistics, Computer Science, Informatics, Mathematics or similar field. Specifically, a PhD with 5+ years of relevant experience (beyond dissertation work), or Master's degree with 7+ years of relevant experience. Bachelor's degree in related field with 10+ years of relevant experience will also be considered.
Preferred prior experience in the pharmaceutical/biotechnology/healthcare/health IT industry, at least 2+ years of hands-on experience executing observational healthcare or translational research studies, as well as 2+ years of hands-on experience working with large real world databases (EMR, biobanks, consortium data, etc).
Technical Experience Guidelines:


Advanced hands-on knowledge of SAS, R and/or Python
Experience analyzing data from traditional healthcare databases (electronic medical records, claims, etc) and integrated omics data is preferred
Experience working in Cloud Computing environments (ex AWS, Azure, etc) is preferred




Reference: 1152695536

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