Quantitative Analytics & Model Analyst Senior - Data Operations and Machine Learning Operations
East Brunswick, NJAll locationsEast Brunswick, NJVA - Tysons CornerDC - Washington (20006)Pittsburgh, PAOH - Cleveland (44114) On-site
$86,250–$172,500 a yearJobFig found this opening at its original source and checks that it remains available.
About the role
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; Washington, DC; East Brunswick, NJ; or Tyson's Corner, VA. 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. PNC Employees take pride in our reputation and to continue building upon that we expect our employees to be: Salaries may vary based on geographic location, market data and on individual skills, experience, and education. This role is incentive eligible with the payment based upon company, business and/or individual performance.
What you'll bring
- 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