Quantitative Analytics & Model Analyst Senior - Data Operations and Machine Learning Operations

Overview At PNC, our people are our greatest differentiator and competitive advantage in the markets we serve. We are all united in delivering the best experience for our customers. We work together each day to foster an inclusive workplace culture where all of our employees feel respected, valued and have an opportunity to contribute to the company’s success. As a Quantitative Analytics & Model Analyst Senior within PNC's Data Operations and Machine Learning Operations organization, you will be based in Pittsburgh, PA; Cleveland, OH; or Tyson's Corner, VA.

Overview: PNC is seeking a Quantitative Analytics & Model Analyst Senior to join our Data Operations and Machine Learning Operations (MLOps) team. This role is responsible for designing, engineering, deploying, and supporting scalable AI and machine learning solutions that enable advanced analytics across the enterprise. The successful candidate will combine expertise in system engineering, cloud infrastructure, DevOps, and machine learning operations to help transition analytical and machine learning solutions from development into production environments. This individual will partner closely with data scientists, technology teams, business stakeholders, and lines of business to ensure AI and ML solutions are reliable, scalable, secure, and operationally efficient. Key Responsibilities: • Build scalable frameworks and reusable components that support model development, integration, testing, deployment, and monitoring. • Collaborate with data scientists to operate analytical and machine learning solutions across production environments. • Support model lifecycle management, including deployment, testing, validation, performance monitoring, and ongoing optimization • Assist in managing model releases, version control, and deployment processes. • Partner with engineering teams to establish infrastructure standards for model deployment and operational support. • Support automation, orchestration, and infrastructure-as-code initiatives where applicable. • Troubleshoot deployment, integration, and operational issues across AI/ML ecosystems • Partner with business leaders, technology teams, data scientists, and other Lines of Business to understand requirements and deliver solutions. Required Qualifications: • Bachelor’s degree in computer science, Information Systems, Data Science, Engineering, Mathematics, Statistics, or a related quantitative field. • Design and engineer AI / ML solutions, including ML models, GenAI applications, and agentic AI capabilities that address complex data science and business use cases • Build scalable frameworks and reusable components for developing, integrating, testing, and deploying ML models and AI agents across the data science lifecycle • Develop, validate, and test container images in OpenShift Container Platform (OCP) to ensure AI / ML models, agentic solutions, and supporting components can be reliably packaged and deployed across environments • Experience supporting machine learning, analytics, software engineering, DevOps, or MLOps environments. • Experience deploying and supporting analytical or machine learning solutions in enterprise environments. • Programming/Coding experience in Python, R, or PySpark. • Working knowledge of SQL, including the ability to understand, review, and manipulate SQL code. • Experience with source control, CI/CD, and deployment tools, including Git, Jenkins, Docker, JIRA, or Confluence. • Experience with Cloud Platforms: AWS or Azure • Experience supporting code deployment and release management processes. • Understanding of machine learning workflows and model deployment concepts • Strong analytical and problem-solving skills. • Excellent communication and presentation skills • Ability to influence and collaborate across technical and business teams. • Experience working in highly collaborative, cross-functional environments • Strong