Senior Director, Data Sciences and Advanced Analytics
Bristol Myers Squibb
6 months ago
Remote friendly (Cambridge, MA)
United States
IT
Senior Director, Data Sciences and Advanced Analytics (DSAA)
Responsibilities
- Lead a team of ~5 individuals to drive data science objectives across early to late-phase drug development in a specific therapeutic area.
- Drive exploratory analysis to support drug development and clinical study design decisions.
- Define approaches, processes, algorithms, and tools for analytics, visualizations, and decision support for drug development scientists and projects.
- Integrate, mine, and visualize diverse, high-dimensional data sets.
- Develop and apply computational methods for patient segmentation using multimodal clinical and omics datasets (with Translational, Informatics, Clinical, and Statistical scientists).
- Develop, validate, and implement predictive models; deploy automated processes to produce modeling results at scale.
- Generate data-driven insights and present them through intuitive visualizations.
- Collaborate across teams; ensure connectivity of exploratory analysis work for development, regulatory approval, and market acceptance.
- Ensure quality of deliverables by applying analysis/reporting standards and complying with regulatory requirements, corporate/department SOPs, and work practices.
- Drive innovative strategies/technologies.
- Independently develop, troubleshoot, and maintain complex programs/utilities per specifications and BMS standards.
- Provide technical guidance to external partners on project/data standards and analysis practices.
- Understand and apply software development methodologies.
- Identify opportunities to improve efficiency/consistency within DSAA; provide SME support for continuous improvement.
Qualifications
- PhD in a relevant quantitative field (e.g., Biostatistics, Statistics, Bioinformatics, Computer Science).
- 10+ years of relevant experience after receiving a graduate degree.
Required skills/competencies
- Mastery of data analysis using clinical trials, observational research, and real-world data; modeling for clinical trials.
- Strong expertise in AI/DL/ML algorithms.
- Background in core statistical methods (e.g., generalized linear/nonlinear models, survival analysis).
- Experience in oncology, neuroscience, and immunology.
- Expertise with imaging, genomics, and proteomics data.
- Strong technical/analytic skills; ability to define business problems and implement analytic/decision-support solutions.
- Leadership, communication, organizational, and interpersonal skills; able to interface across R&D.
- Ability to explain complex technical information to non-technical audiences.
- Proven ability to develop/execute strategic long-range plans.
- Strong programming knowledge (R, Python) in HPC environments (e.g., AWS).
- Knowledge of industry practices and regulatory requirements.
- Ability to travel up to 20%.
Preferred skills
- Experience with NLP.
Application instructions
- If needed, apply even if you don’t perfectly match the resume requirements.
Responsibilities
- Lead a team of ~5 individuals to drive data science objectives across early to late-phase drug development in a specific therapeutic area.
- Drive exploratory analysis to support drug development and clinical study design decisions.
- Define approaches, processes, algorithms, and tools for analytics, visualizations, and decision support for drug development scientists and projects.
- Integrate, mine, and visualize diverse, high-dimensional data sets.
- Develop and apply computational methods for patient segmentation using multimodal clinical and omics datasets (with Translational, Informatics, Clinical, and Statistical scientists).
- Develop, validate, and implement predictive models; deploy automated processes to produce modeling results at scale.
- Generate data-driven insights and present them through intuitive visualizations.
- Collaborate across teams; ensure connectivity of exploratory analysis work for development, regulatory approval, and market acceptance.
- Ensure quality of deliverables by applying analysis/reporting standards and complying with regulatory requirements, corporate/department SOPs, and work practices.
- Drive innovative strategies/technologies.
- Independently develop, troubleshoot, and maintain complex programs/utilities per specifications and BMS standards.
- Provide technical guidance to external partners on project/data standards and analysis practices.
- Understand and apply software development methodologies.
- Identify opportunities to improve efficiency/consistency within DSAA; provide SME support for continuous improvement.
Qualifications
- PhD in a relevant quantitative field (e.g., Biostatistics, Statistics, Bioinformatics, Computer Science).
- 10+ years of relevant experience after receiving a graduate degree.
Required skills/competencies
- Mastery of data analysis using clinical trials, observational research, and real-world data; modeling for clinical trials.
- Strong expertise in AI/DL/ML algorithms.
- Background in core statistical methods (e.g., generalized linear/nonlinear models, survival analysis).
- Experience in oncology, neuroscience, and immunology.
- Expertise with imaging, genomics, and proteomics data.
- Strong technical/analytic skills; ability to define business problems and implement analytic/decision-support solutions.
- Leadership, communication, organizational, and interpersonal skills; able to interface across R&D.
- Ability to explain complex technical information to non-technical audiences.
- Proven ability to develop/execute strategic long-range plans.
- Strong programming knowledge (R, Python) in HPC environments (e.g., AWS).
- Knowledge of industry practices and regulatory requirements.
- Ability to travel up to 20%.
Preferred skills
- Experience with NLP.
Application instructions
- If needed, apply even if you don’t perfectly match the resume requirements.