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

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

Job Description

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; Washington, DC; East Brunswick, NJ; or Tyson's Corner, VA.

Position 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 stakeholder engagement and relationship management capabilities.

Preferred Qualifications

• Banking, financial services, lending, or risk management experience.
• Familiarity with model governance, model monitoring, and production support processes.
• Understanding of data engineering and enterprise data ecosystems

Job Description

• Independently performs advanced quantitative analyses and model development to drive decision-making by running quantitative strategies. Makes recommendations based on analyses.
• Analyzes and develops new model frameworks by supporting the line of business. Refines, monitors, and reviews existing models. Conducts on-going communication with model owners and model developers during the course of the review. Works with larger, more complex datasets to create models.
• Performs quantitative analysis and develops complex reports. Performs qualitative and quantitative assessments of all aspects of models including theoretical aspects, model design and implementation as well as data quality and integrity. Analyzes complex data and associated quantitative analysis. Makes recommendations based on findings from data analytics.
• Uses quantitative tools and techniques to measure and analyze model risks and reaches conclusions on strengths and limitations of the model.
• Prepares and analyzes detailed documents for validation and regulatory compliance, using applicable templates.

Employees take pride in our reputation and to continue building upon that we expect our employees to be:

• Customer Focused - Knowledgeable of the values and practices that align customer needs and satisfaction as primary considerations in all business decisions and able to leverage that information in creating customized customer solutions.
• Managing Risk - Assessing and effectively managing all of the risks associated with their business objectives and activities to ensure they adhere to and support PNC's Enterprise Risk Management Framework.

Qualifications

Successful candidates must demonstrate appropriate knowledge, skills, and abilities for a role. Listed below are skills, competencies, work experience, education, and required certifications/licensures needed to be successful in this position.

SkillsAnalytical Thinking, Credit Risks, Data Analytics, Financial Analysis, Model Development, Operational Risks, Quantitative Models, Risk Appetite

CompetenciesBank Quantitative Analysis, Consulting, Data Gathering and Reporting, Effective Communications, Predictive Analytics, Quantitative Techniques, Regulatory Environment - Financial Services, Testing

Work ExperienceRoles at this level typically require a university / college degree, with 3+ years of relevant / direct industry experience. Certifications are often desired. In lieu of a degree, a comparable combination of education, job specific certification(s), and experience (including military service) may be considered.

EducationBachelors

CertificationsNo Required Certification(s)

LicensesNo Required License(s)

AssessmentsNo Required or Assessments

Pay Transparency

Base Salary: $86,250.00 - $172,500.00

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.

Application Window

Generally, this opening is expected to be posted for two business days from 09/17/2026, although it may be longer with business discretion.

Benefits

PNC offers a comprehensive range of benefits to help meet your needs now and in the future. Depending on your eligibility, options for full-time employees include: medical/prescription drug coverage (with a Health Savings Account feature), dental and vision options; employee and spouse/child life insurance; short and long-term protection; 401(k) with PNC match, pension and stock purchase plans; dependent care reimbursement account; back-up child/elder care; adoption, surrogacy, and doula reimbursement; educational assistance, including select programs fully paid; a robust wellness program with financial incentives.

In addition, PNC generally provides the following paid time off, depending on your eligibility: maternity and/or parental leave; up to 11 paid holidays each