Senior Director, Data Sciences and Advanced Analytics
Bristol Myers Squibb
5 months ago
Remote friendly (Princeton, NJ)
United States
IT
Responsibilities:
- Lead a team (~5) driving data science objectives across early to late-phase drug development in a therapeutic area.
- Execute exploratory analysis (hypothesis generation/testing questions) and define analytics approaches, processes, algorithms, and tools for decision support.
- Integrate, mine, and visualize diverse, high-dimensional datasets.
- Develop/apply computational methods for patient segmentation from multimodal clinical and omics data.
- Develop/validate predictive models and deploy automated processes for scalable modeling.
- Generate insights and present via rich, intuitive visualizations.
- Ensure deliverable quality and compliance with regulatory requirements, SOPs, and work practices.
- Drive innovative strategies/technologies; independently develop and maintain complex programs/utilities.
- Provide technical guidance to external partners on project/data standards and analysis practices.
- Apply software development methodologies; identify DSAA efficiency improvements and support continuous improvement.
Key Requirements:
- PhD in a relevant quantitative field (e.g., Biostatistics, Statistics, Bioinformatics, Computer Science).
- 10+ years of relevant experience after graduate degree.
Required/Preferred Skills:
- Advanced data analysis for clinical trials/observational/real-world data; strong AI/DL/ML.
- Core statistics (e.g., generalized linear/nonlinear models, survival analysis).
- Disease area experience: oncology, neuroscience, immunology.
- Experience with imaging/genomics/proteomics.
- Strong programming (R, Python) in HPC (e.g., AWS); NLP experience preferred.
- Leadership, communication, strategic planning, ability to explain complex topics to non-technical audiences.
Travel:
- Up to 20%.
Benefits (explicitly listed):
- Health coverage; wellbeing support; 401(k) and other financial protection.
- Paid time off (flexible time off and other PTO structures depending on location/role type).
- Lead a team (~5) driving data science objectives across early to late-phase drug development in a therapeutic area.
- Execute exploratory analysis (hypothesis generation/testing questions) and define analytics approaches, processes, algorithms, and tools for decision support.
- Integrate, mine, and visualize diverse, high-dimensional datasets.
- Develop/apply computational methods for patient segmentation from multimodal clinical and omics data.
- Develop/validate predictive models and deploy automated processes for scalable modeling.
- Generate insights and present via rich, intuitive visualizations.
- Ensure deliverable quality and compliance with regulatory requirements, SOPs, and work practices.
- Drive innovative strategies/technologies; independently develop and maintain complex programs/utilities.
- Provide technical guidance to external partners on project/data standards and analysis practices.
- Apply software development methodologies; identify DSAA efficiency improvements and support continuous improvement.
Key Requirements:
- PhD in a relevant quantitative field (e.g., Biostatistics, Statistics, Bioinformatics, Computer Science).
- 10+ years of relevant experience after graduate degree.
Required/Preferred Skills:
- Advanced data analysis for clinical trials/observational/real-world data; strong AI/DL/ML.
- Core statistics (e.g., generalized linear/nonlinear models, survival analysis).
- Disease area experience: oncology, neuroscience, immunology.
- Experience with imaging/genomics/proteomics.
- Strong programming (R, Python) in HPC (e.g., AWS); NLP experience preferred.
- Leadership, communication, strategic planning, ability to explain complex topics to non-technical audiences.
Travel:
- Up to 20%.
Benefits (explicitly listed):
- Health coverage; wellbeing support; 401(k) and other financial protection.
- Paid time off (flexible time off and other PTO structures depending on location/role type).