Senior Manager: Knowledge Systems

About the role

The Product Development and Supply (PDS) Analytics & AI Enablement (A&AIE) is part of the Business Insights and Technology (BIT) at Bristol Myers Squibb. This role supports drug development from discovery through commercialization and distribution to patients. Key responsibilities include deploying, monitoring, and automating analytics assets in production, ensuring their reliability, scalability, and performance.

Responsibilities

• Ensure analytics assets are reliably and efficiently deployed and maintained in production.
• Set up continuous integration pipelines to automate testing, validation, and deployment of analytics assets.
• Implement automated monitoring and alerting systems to address disruptions or anomalies promptly.
• Collaborate with data engineers and scientists to integrate data and model requirements into production systems.
• Troubleshoot and resolve complex issues related to deployment, performance, and scalability.
• Develop governance policies for data management, model development, and analytics deployment.
• Scale best practices across the organization for consistency and efficiency.
• Implement robust security measures to protect data assets.
• Participate in decision-making and bring a variety of strong views and perspectives to achieve team objectives.
• Lead in analyzing current states, delivering strong recommendations, and executing complex solutions.

Qualifications & Experience

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• 5+ years of experience in deploying and managing models in production environments.
• Experience leading initiatives related to continuous improvement or implementation of MLOps.
• Strong understanding of machine learning principles and model lifecycle management.
• Strong programming skills in languages such as Python, PySpark, SQL, Bash/PowerShell.
• Extensive experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Proficiency in cloud platforms (e.g., AWS is preferred, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes).
• Expertise in CI/CD tools (e.g., Jenkins, GitLab CI, CircleCI) and version control systems (e.g., Git).
• In-depth knowledge of monitoring and logging tools (e.g., CloudWatch, Grafana, ELK stack).
• Strong problem-solving skills and ability to work in a fast-paced, collaborative environment.
• Excellent communication skills and ability to articulate and present complex information clearly and concisely.
• Demonstrated ability to analyze complex information and provide strong recommendations.