Bristol-Myers Squibb Company

Center for Observational Research and Data Science - Data Scientist

Princeton, NJ, US
Jul 27, 2018
Required Education
Masters Degree/MBA
Position Type
Full time
The Center for Observational Research and Data Science (CORDS) - Data Scientist role is an individual contributor that will be part of a newly established advanced analytics lab that supports BMS's digital health initiatives. This is a highly visible position where the successful candidate will provide technical leadership to multi-disciplinary projects contributing to a range of research and development (R&D) activities within BMS. We are looking for a hands-on data scientist who will build solutions to solve digital health-related problems such as predicting patient outcomes, creating novel data sources, identification of novel predictors, automating analysis and building interactive visualizations.

Core Responsibilities
  • Contribute to projects implementing predictive models using tools such as classification, survival analysis, time-series analysis and clustering to solve digital health business problems. Develop visualizations to effectively convey insights.
  • Establish novel data resources and predictors through processing of a variety of sources that could include medical records and reports, insurance claims, lab results, genomics and medical imagery.
  • Provide guidance on the application of established, new and emerging machine learning, AI and data visualization methods and tools to the BMS analytics community.
  • Complete other duties as assigned by Advanced Analytics Lead, CORDS

Experiences Required for Success
  • Experience applying data science methods and tools to diverse problems using R and/or Python. Experience applying deep learning tools such as TensorFlow, Keras, Theano and/or experience in the application of NLP will be highly regarded.
  • Experience in efficiently extracting data from a range of structured and unstructured sources.
  • Ability to develop high quality static and interactive visualizations using tools such as Tableau, ggplot, Plotly, Shiny or similar.
  • Proven strong writing and oral presentation skills and the ability to explain complex concepts to colleagues with varying degrees of technical knowledge.
  • Exposure to real world healthcare data, pharmaceutical industry research activities, and clinical research data (biomarkers, -omics data) will looked upon favorably.

Knowledge Desired
  • A Master's degree or higher (PhD will be highly regarded) in data science, AI or a related quantitative field.
  • Strong technical and scientific knowledge in research methods applied to healthcare including non-interventional scientific disciplines
  • Awareness of the drug development & commercialization process, HTA assessment methodologies, global reimbursement environment, and regulatory requirements.
  • Knowledge of the pharmaceutical industry and competitors (their strategy, drug discovery, the drugs, CR&D, outcomes research and marketing).