Senior Quant Analytics & MLOps Specialist

Energy Jobline ZR; Cleveland (OH); On-site; USD 86,000 - 173,000; Full time

Benefits offered by this job

Medical benefits

401(k) with match

Paid holidays

Job summary

PNC is seeking a Quantitative Analytics & Model Analyst Senior to join the Data Operations and Machine Learning Operations team. You will design, engineer, deploy, and support scalable AI and ML solutions across the enterprise, partnering with data scientists and engineers to ensure reliable production systems.

The role requires expertise in system engineering, cloud infrastructure, DevOps, and ML operations to transition solutions from development to production while maintaining security,

Qualifications

• Bachelor’s degree in computer science, information systems, data science, engineering, mathematics or a related quantitative field.
• Experience designing and engineering AI/ML solutions including models and GenAI applications.
• Experience with containerized ML workflows and production deployment.
• Experience with source control, CI/CD, and deployment tools (Git, Jenkins, Docker).
• Experience with cloud platforms (AWS or Azure).
• Strong analytical and problem-solving skills.

Responsibilities

• Design, engineer, deploy, and support scalable AI/ML solutions.
• Collaborate with data scientists and engineers to deploy models in production.
• Manage model lifecycle, testing, validation, and performance monitoring.
• Coordinate deployments and release management.
• Implement infrastructure standards for model deployment and ops.
• Support automation and IaC initiatives.

Skills

Python/R/PySpark

SQL

Git/Jenkins/Docker/JIRA/Confluence

Cloud Platforms AWS/Azure

OpenShift

DevOps/MLOps

Communication/Stakeholder management

Education

Bachelor’s degree in computer science/related quantitative field

Tools

OpenShift Container Platform

Job description

PNC is seeking a Quantitative Analytics & Model Analyst Senior to join the Data Operations and Machine Learning Operations team. You will design, engineer, deploy, and support scalable AI and ML solutions across the enterprise, partnering with data scientists and engineers to ensure reliable production systems.

The role requires expertise in system engineering, cloud infrastructure, DevOps, and ML operations to transition solutions from development to production while maintaining security,