Bristol Myers Squibb is looking to extract insight from complex clinical, translational, and real-world data to solve complex data science problems, including modeling techniques to interpret, infer, and recommend based on data insights.
Requirements
- Strong knowledge of programing languages, with a focus on machine learning (Python, Spark, R, Tensorflow, Sagemaker, etc)
- Proven data driven problem solving capabilities using AI/ML approaches
- Experience with longitudinal real-world patient data analysis
- Experience with next generation sequencing (omics) translational data analysis
- Experience in using deep learning-based algorithms in one of the following areas - image analysis, clinical NLP, physiological waveforms, genomic or clinical data
Responsibilities
- Formulates, implements, tests, and validates predictive models and implements efficient automated processes for producing modeling resules at scale.
- Creates robust models based on statistical and data mining techniques to provide insights and recommendations based on large complex data sets.
- Presents stories told by data in a visually appealing and easy to understand manner.
Other
- Currently in a quantitative sciences PhD program ( Computer Science, Math, Computational Biology)
- Demonstrated passion for healthcare
- All candidates must be authorized to work in the US both at the time of hire and for the duration of their employment. Please note that immigration or visa sponsorship is not available for this position.
- This is a temporary, time-bound position intended for the duration of the internship or co-op program. Employment in this role does not imply or guarantee ongoing or permanent employment with BMS.
- The full-time internship will take place June - August 2026.
