Senior Manager, Analytical AI Clinical Development
Bristol-Myers Squibb
Senior Manager, Analytical AI Clinical Development
Job Description
1. Develop and Deploy Machine Learning Pipelines: Apply expertise in machine learning to create, implement, and optimize end-to-end pipelines that address critical business problems in clinical study design and execution. Automate workflows to process and analyze complex datasets, such as clinical trial protocols, real-world evidence, and patient recruitment data. Ensure the scalability, reliability, and robustness of deployed machine learning solutions for real-time decision support. Manage AI Product Lifecycle: Develop and execute detailed project plans that align with clinical development timelines, ensuring timely delivery of AI solutions. Work-life programs include paid national holidays and optional holidays, Global Shutdown Days between Christmas and New Year's holiday, up to 120 hours of paid vacation, up to two (2) paid days to volunteer, sick time off, and summer hours flexibility. BA/BS in a quantitative field such as data science, computer science, mathematics, or related disciplines. Advanced degrees (MBA, MS, or Ph.D.) in a relevant field (computer science/computational biology/bioinformatics etc.) preferred. Minimum of 3 years of hands-on experience developing and deploying machine learning pipelines to solve real-world business problems. Proven ability to deliver measurable impact through AI and advanced analytics solutions. Strong foundation in statistical methods and their application to business problems, preferably in a clinical development setting Experience designing and implementing supervised, unsupervised and reinforcement learning methods with common machine learning frameworks (TensorFlow, PyTorch, scikit-learn etc.) Experience with time series forecasting and Monte Carlo simulations Proficiency in Python and SQL is required Familiarity with CI/CD workflows and Git/GitHub for version control. Familiarity with MLOps workflows, cloud-based environments (e.g., AWS, Azure) and workflow orchestration tools (e.g., Airflow, Dagster). Experience with Natural Language Processing techniques and Large Language Models is highly preferred Experience working with real-world datasets (RWD) is highly preferred Experience in bioinformatics/computational biology is a plus Experience with Streamlit/Dash/Shiny app development is a plus Excellent communication and presentation skills, with a proven ability to translate technical complexity into clear, actionable insights for diverse audiences. Strong leadership and interpersonal skills to foster stakeholder engagement and cross-functional collaboration. Knowledge of drug development and clinical trial operations is highly desirable. Experience managing AI product lifecycles and integrating solutions into business operations.
Key Responsibilities
- Develop and deploy machine learning pipelines to address critical business problems in clinical study design and execution
- Automate workflows to process and analyze complex datasets, such as clinical trial protocols, real-world evidence, and patient recruitment data
- Ensure the scalability, reliability, and robustness of deployed machine learning solutions for real-time decision support
- Manage AI product lifecycle, developing and executing detailed project plans that align with clinical development timelines
- Ensure timely delivery of AI solutions
- Integrate AI solutions into business operations
Required Qualifications
- BA/BS in a quantitative field such as data science, computer science, mathematics, or related disciplines
- Minimum of 3 years of hands-on experience developing and deploying machine learning pipelines to solve real-world business problems
- Proven ability to deliver measurable impact through AI and advanced analytics solutions
- Strong foundation in statistical methods and their application to business problems, preferably in a clinical development setting
- Experience designing and implementing supervised, unsupervised and reinforcement learning methods with common machine learning frameworks (TensorFlow, PyTorch, scikit-learn etc.)
- Experience with time series forecasting and Monte Carlo simulations
- Proficiency in Python and SQL
Preferred Qualifications
- Advanced degrees (MBA, MS, or Ph.D.) in a relevant field (computer science/computational biology/bioinformatics etc.)
- Experience with Natural Language Processing techniques and Large Language Models
- Experience working with real-world datasets (RWD)
- Experience in bioinformatics/computational biology
- Experience with Streamlit/Dash/Shiny app development
- Knowledge of drug development and clinical trial operations
Skills Required
- Familiarity with CI/CD workflows and Git/GitHub for version control
- Familiarity with MLOps workflows, cloud-based environments (e.g., AWS, Azure) and workflow orchestration tools (e.g., Airflow, Dagster)
- Excellent communication and presentation skills, with a proven ability to translate technical complexity into clear, actionable insights for diverse audiences
- Strong leadership and interpersonal skills to foster stakeholder engagement and cross-functional collaboration
Benefits & Perks
- Paid national holidays and optional holidays
- Global Shutdown Days between Christmas and New Year's holiday
- Up to 120 hours of paid vacation
- Up to two (2) paid days to volunteer
- Sick time off
- Summer hours flexibility
Locations
- Princeton NJ, United States
Salary
Estimated Salary Rangemedium confidence
150,000 - 250,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Familiarity with CI/CD workflows and Git/GitHub for version controlintermediate
- Familiarity with MLOps workflows, cloud-based environments (e.g., AWS, Azure) and workflow orchestration tools (e.g., Airflow, Dagster)intermediate
- Excellent communication and presentation skills, with a proven ability to translate technical complexity into clear, actionable insights for diverse audiencesintermediate
- Strong leadership and interpersonal skills to foster stakeholder engagement and cross-functional collaborationintermediate
Required Qualifications
- BA/BS in a quantitative field such as data science, computer science, mathematics, or related disciplines (experience)
- Minimum of 3 years of hands-on experience developing and deploying machine learning pipelines to solve real-world business problems (experience)
- Proven ability to deliver measurable impact through AI and advanced analytics solutions (experience)
- Strong foundation in statistical methods and their application to business problems, preferably in a clinical development setting (experience)
- Experience designing and implementing supervised, unsupervised and reinforcement learning methods with common machine learning frameworks (TensorFlow, PyTorch, scikit-learn etc.) (experience)
- Experience with time series forecasting and Monte Carlo simulations (experience)
- Proficiency in Python and SQL (experience)
Preferred Qualifications
- Advanced degrees (MBA, MS, or Ph.D.) in a relevant field (computer science/computational biology/bioinformatics etc.) (experience)
- Experience with Natural Language Processing techniques and Large Language Models (experience)
- Experience working with real-world datasets (RWD) (experience)
- Experience in bioinformatics/computational biology (experience)
- Experience with Streamlit/Dash/Shiny app development (experience)
- Knowledge of drug development and clinical trial operations (experience)
Responsibilities
- Develop and deploy machine learning pipelines to address critical business problems in clinical study design and execution
- Automate workflows to process and analyze complex datasets, such as clinical trial protocols, real-world evidence, and patient recruitment data
- Ensure the scalability, reliability, and robustness of deployed machine learning solutions for real-time decision support
- Manage AI product lifecycle, developing and executing detailed project plans that align with clinical development timelines
- Ensure timely delivery of AI solutions
- Integrate AI solutions into business operations
Benefits
- general: Paid national holidays and optional holidays
- general: Global Shutdown Days between Christmas and New Year's holiday
- general: Up to 120 hours of paid vacation
- general: Up to two (2) paid days to volunteer
- general: Sick time off
- general: Summer hours flexibility
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Senior Manager, Analytical AI Clinical Development
Bristol-Myers Squibb
Senior Manager, Analytical AI Clinical Development
Job Description
1. Develop and Deploy Machine Learning Pipelines: Apply expertise in machine learning to create, implement, and optimize end-to-end pipelines that address critical business problems in clinical study design and execution. Automate workflows to process and analyze complex datasets, such as clinical trial protocols, real-world evidence, and patient recruitment data. Ensure the scalability, reliability, and robustness of deployed machine learning solutions for real-time decision support. Manage AI Product Lifecycle: Develop and execute detailed project plans that align with clinical development timelines, ensuring timely delivery of AI solutions. Work-life programs include paid national holidays and optional holidays, Global Shutdown Days between Christmas and New Year's holiday, up to 120 hours of paid vacation, up to two (2) paid days to volunteer, sick time off, and summer hours flexibility. BA/BS in a quantitative field such as data science, computer science, mathematics, or related disciplines. Advanced degrees (MBA, MS, or Ph.D.) in a relevant field (computer science/computational biology/bioinformatics etc.) preferred. Minimum of 3 years of hands-on experience developing and deploying machine learning pipelines to solve real-world business problems. Proven ability to deliver measurable impact through AI and advanced analytics solutions. Strong foundation in statistical methods and their application to business problems, preferably in a clinical development setting Experience designing and implementing supervised, unsupervised and reinforcement learning methods with common machine learning frameworks (TensorFlow, PyTorch, scikit-learn etc.) Experience with time series forecasting and Monte Carlo simulations Proficiency in Python and SQL is required Familiarity with CI/CD workflows and Git/GitHub for version control. Familiarity with MLOps workflows, cloud-based environments (e.g., AWS, Azure) and workflow orchestration tools (e.g., Airflow, Dagster). Experience with Natural Language Processing techniques and Large Language Models is highly preferred Experience working with real-world datasets (RWD) is highly preferred Experience in bioinformatics/computational biology is a plus Experience with Streamlit/Dash/Shiny app development is a plus Excellent communication and presentation skills, with a proven ability to translate technical complexity into clear, actionable insights for diverse audiences. Strong leadership and interpersonal skills to foster stakeholder engagement and cross-functional collaboration. Knowledge of drug development and clinical trial operations is highly desirable. Experience managing AI product lifecycles and integrating solutions into business operations.
Key Responsibilities
- Develop and deploy machine learning pipelines to address critical business problems in clinical study design and execution
- Automate workflows to process and analyze complex datasets, such as clinical trial protocols, real-world evidence, and patient recruitment data
- Ensure the scalability, reliability, and robustness of deployed machine learning solutions for real-time decision support
- Manage AI product lifecycle, developing and executing detailed project plans that align with clinical development timelines
- Ensure timely delivery of AI solutions
- Integrate AI solutions into business operations
Required Qualifications
- BA/BS in a quantitative field such as data science, computer science, mathematics, or related disciplines
- Minimum of 3 years of hands-on experience developing and deploying machine learning pipelines to solve real-world business problems
- Proven ability to deliver measurable impact through AI and advanced analytics solutions
- Strong foundation in statistical methods and their application to business problems, preferably in a clinical development setting
- Experience designing and implementing supervised, unsupervised and reinforcement learning methods with common machine learning frameworks (TensorFlow, PyTorch, scikit-learn etc.)
- Experience with time series forecasting and Monte Carlo simulations
- Proficiency in Python and SQL
Preferred Qualifications
- Advanced degrees (MBA, MS, or Ph.D.) in a relevant field (computer science/computational biology/bioinformatics etc.)
- Experience with Natural Language Processing techniques and Large Language Models
- Experience working with real-world datasets (RWD)
- Experience in bioinformatics/computational biology
- Experience with Streamlit/Dash/Shiny app development
- Knowledge of drug development and clinical trial operations
Skills Required
- Familiarity with CI/CD workflows and Git/GitHub for version control
- Familiarity with MLOps workflows, cloud-based environments (e.g., AWS, Azure) and workflow orchestration tools (e.g., Airflow, Dagster)
- Excellent communication and presentation skills, with a proven ability to translate technical complexity into clear, actionable insights for diverse audiences
- Strong leadership and interpersonal skills to foster stakeholder engagement and cross-functional collaboration
Benefits & Perks
- Paid national holidays and optional holidays
- Global Shutdown Days between Christmas and New Year's holiday
- Up to 120 hours of paid vacation
- Up to two (2) paid days to volunteer
- Sick time off
- Summer hours flexibility
Locations
- Princeton NJ, United States
Salary
Estimated Salary Rangemedium confidence
150,000 - 250,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Familiarity with CI/CD workflows and Git/GitHub for version controlintermediate
- Familiarity with MLOps workflows, cloud-based environments (e.g., AWS, Azure) and workflow orchestration tools (e.g., Airflow, Dagster)intermediate
- Excellent communication and presentation skills, with a proven ability to translate technical complexity into clear, actionable insights for diverse audiencesintermediate
- Strong leadership and interpersonal skills to foster stakeholder engagement and cross-functional collaborationintermediate
Required Qualifications
- BA/BS in a quantitative field such as data science, computer science, mathematics, or related disciplines (experience)
- Minimum of 3 years of hands-on experience developing and deploying machine learning pipelines to solve real-world business problems (experience)
- Proven ability to deliver measurable impact through AI and advanced analytics solutions (experience)
- Strong foundation in statistical methods and their application to business problems, preferably in a clinical development setting (experience)
- Experience designing and implementing supervised, unsupervised and reinforcement learning methods with common machine learning frameworks (TensorFlow, PyTorch, scikit-learn etc.) (experience)
- Experience with time series forecasting and Monte Carlo simulations (experience)
- Proficiency in Python and SQL (experience)
Preferred Qualifications
- Advanced degrees (MBA, MS, or Ph.D.) in a relevant field (computer science/computational biology/bioinformatics etc.) (experience)
- Experience with Natural Language Processing techniques and Large Language Models (experience)
- Experience working with real-world datasets (RWD) (experience)
- Experience in bioinformatics/computational biology (experience)
- Experience with Streamlit/Dash/Shiny app development (experience)
- Knowledge of drug development and clinical trial operations (experience)
Responsibilities
- Develop and deploy machine learning pipelines to address critical business problems in clinical study design and execution
- Automate workflows to process and analyze complex datasets, such as clinical trial protocols, real-world evidence, and patient recruitment data
- Ensure the scalability, reliability, and robustness of deployed machine learning solutions for real-time decision support
- Manage AI product lifecycle, developing and executing detailed project plans that align with clinical development timelines
- Ensure timely delivery of AI solutions
- Integrate AI solutions into business operations
Benefits
- general: Paid national holidays and optional holidays
- general: Global Shutdown Days between Christmas and New Year's holiday
- general: Up to 120 hours of paid vacation
- general: Up to two (2) paid days to volunteer
- general: Sick time off
- general: Summer hours flexibility
Tags & Categories
Answer 10 quick questions to check your fit for Senior Manager, Analytical AI Clinical Development @ Bristol-Myers Squibb.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs