Quantitative Analytics & Model Analyst Senior - Credit Loss Forecasting (CLF)

Position 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 Credit Loss Forecasting (CLF) organization, you will be based in Pittsburgh, PA; Cleveland, or Columbus, OH; Tyson's Corner, VA; Charlotte, NC; East Brunswick, NJ; or Washington, DC. Job Summary: The Quantitative Analytics & Model Analyst Senior will support the development, implementation, monitoring, and governance of quantitative models and analytical processes used for CECL, CCAR, and Model Monitoring initiatives. This role requires strong technical expertise in Python development, data engineering, quantitative analytics, and process automation. The successful candidate will partner closely with modeling, technology, and business teams to deliver scalable analytical solutions, enhance model processes, and ensure compliance with regulatory and governance requirements. Key Responsibilities: •Develop, maintain, and enhance analytical processes, controls, and supporting infrastructure for CECL, CCAR, Model Monitoring, and other regulatory initiatives. •Collaborate with model development and validation teams to support model implementation, onboarding, testing, monitoring, and production deployment. •Design, develop, and maintain robust Python-based solutions to automate data processing, analytics workflows, controls, and reporting processes. •Troubleshoot and resolve complex technical issues related to model execution, data quality, workflow orchestration, and analytical outputs. •Perform quantitative analysis on large and complex datasets to identify trends, validate model performance, and support business decision-making. •Implement and optimize data pipelines using modern analytics and distributed computing frameworks. •Leverage AI, machine learning, and advanced analytical techniques to improve process efficiency, model monitoring capabilities, and analytical insights. •Support model governance activities, including documentation, testing, validation support, issue remediation, control execution, and audit/regulatory inquiries. •Partner with cross-functional teams to ensure analytical solutions align with business objectives, risk management practices, and regulatory requirements. •Communicate analytical findings, technical issues, and recommendations to both technical and non-technical stakeholders. Required Qualifications: •Bachelor's or Master's degree in Quantitative Finance, Statistics, Mathematics, Computer Science, Data Science, Engineering, or a related quantitative field. •Strong Python programming and software development experience. •Experience working with large-scale datasets and data manipulation frameworks. •Strong problem-solving skills with the ability to diagnose and resolve complex analytical and technical issues. •Experience developing automated solutions and analytical workflows. •Strong communication and collaboration skills. Preferred Qualifications: •Experience with Python, PySpark, Git/Bitbucket, and cloud or distributed computing environments. •Experience supporting quantitative models within financial services. •Knowledge of CECL, CCAR, stress testing, model monitoring, model governance, or regulatory reporting processes. •Exposure to machine learning, AI, predictive modeling, or advanced analytics techniques. •Understanding of banking products, credit risk, and regulatory frameworks. •Experience working in highly regulated environments. •Financial services experience preferred. PNC is an in-office company that fosters a supportive culture where employees can thrive and achieve balance. We encourage candidates to connect with their recruiter and hiring manager to understand workplace expectations and ensure the role aligns with their goals. PNC will not provide sponsorship for employment visas or participate in STEM OPT for this position. 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. PNC 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. 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