Senior Manager, Analytical AI - Engineering

Working with Us
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. Read more: careers.bms.com/working-with-us.

Description:  Senior Manager of Analytical AI - Engineering team provides technical expertise to develop, deploy, and maintain data science and machine learning related pipelines, solutions, and products.

Key Responsibilities and Major Duties

• Member of a hands-on team of data engineers and machine learning engineers.

• Work cross functionally with analytics and business stakeholders to rapidly pilot and deploy a wide variety of data science and machine learning solutions.

• Hands-on design, deployment, and maintenance of pipelines for data science related products and machine learning solutions, ensuring reliability, scalability, and maintainability.

• Develop and maintain cutting-edge tools and frameworks empowering data scientists to work efficiently and effectively.

• Develop a close working relationship with data science teams to facilitate and implement best practices relating to machine learning engineering, data engineering, and MLOps.

• Build, deploy, and maintain data science related applications made in frameworks like Dash, Streamlit and R Shiny.

• Apply NLP techniques in support of solving business problems.

Qualifications/Degree/Certification/Licensure

• BA/BS required (quantitative area of study preferred).

• MBA/MS or other graduate degree preferred.

• Minimum of 3 years of experience and relevant advanced degrees contribute to required years of experience.

• Proficiency in Python/R, SQL, Tableau and MS Office Suite.

• Hands on experience with designing and deploying machine learning models using Scikit-Learn, TensorFlow, PyTorch, etc. is preferred.

• Experience with Git.

• Experience with cloud-based environments (AWS, Azure, etc.).

• Experience with MLOps.

• Proven experience in leading large, complex projects with multi-function team members

• Excellent communications and presentation skills.  Proven ability to explain complex analyses and outcomes to both technical and non-technical stakeholders.

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 collaborativ