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

PNC•Tysons, VA

12d•$86,250 - $172,500•Onsite

About The Position

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. 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.

Requirements

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.
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.
University / college degree, with 3+ years of relevant / direct industry experience.
In lieu of a degree, a comparable combination of education, job specific certification(s), and experience (including military service) may be considered.

Nice To Haves

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
Analytical Thinking
Credit Risks
Data Analytics
Financial Analysis
Model Development
Operational Risks
Quantitative Models
Risk Appetite
Bank Quantitative Analysis
Consulting
Data Gathering and Reporting
Effective Communications
Predictive Analytics
Quantitative Techniques
Regulatory Environment - Financial Services
Testing

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.
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.

Benefits

medical/prescription drug coverage (with a Health Savings Account feature)
dental and vision options
employee and spouse/child life insurance
short and long-term disability 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
maternity and/or parental leave
up to 11 paid holidays each year
9 occasional absence days each year, unless otherwise required by law
between 15 to 25 vacation days each year, depending on career level; and years of service.