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Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible.

Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. 

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 Duties

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.

2. Drive Stakeholder Engagement and Collaboration:

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.

3. Manage AI Product Lifecycle:

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.

4. Stay Ahead of AI Trends in Clinical Development:

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.