Description:
Senior Manager - Analytical AI, Clinical Development
Job Position Summary
Aligned with Bristol Myers Squibb's mission to advance clinical development through data-driven innovation, the Senior Manager - Analytical AI in Clinical Development will play a key role in designing and deploying machine learning pipelines to optimize clinical trial operations. This individual will engage with cross-functional stakeholders to deliver impactful AI-based solutions and ensure their seamless integration into business processes, driving efficiency and enhancing decision-making across the drug development portfolio.
Key Responsibilities And Major Duties2. Drive Stakeholder Engagement and Collaboration:3. Manage AI Product Lifecycle:4. Stay Ahead of AI Trends in Clinical Development:Qualifications If you come across a role that intrigues you but doesn't perfectly line up with your resume, we encourage you to apply anyway. You could be one step away from work that will transform your life and career.
- 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.
- Partner with cross-functional teams, including IT, medical, development, and biostatistics groups, to co-develop AI-driven solutions aligned with business priorities.
- Act as liaison between technical teams and non-technical stakeholders, ensuring alignment on objectives and fostering a collaborative environment for successful solution delivery.
- Translate technical insights and model results into actionable strategies for clinical operations teams.
- Oversee the lifecycle of AI products, from ideation and development to deployment and monitoring.
- Develop and execute detailed project plans that align with clinical development timelines, ensuring timely delivery of AI solutions.
- Conduct post-deployment analysis to measure the impact of implemented solutions and identify areas for continuous improvement.
- Continuously evaluate emerging trends and advancements in data science and AI, integrating cutting-edge techniques such as natural language processing (NLP) and predictive analytics into clinical trial workflows.
- Education:
- 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.
- Experience:
- 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.
- Technical Skills:
- 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
- Soft Skills:
- 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.
- Preferred Expertise:
- Knowledge of drug development and clinical trial operations is highly desirable.
- Experience managing AI product lifecycles and integrating solutions into business operations.