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

PNC Business Credit; United States; Remote; USD 86,000 - 173,000; Full time

Job summary

PNC is seeking a Senior Quantitative Analytics & Model Analyst to design, develop, and govern quantitative models and AI-enabled automation for CECL, CCAR, and model monitoring. The role requires hands-on Python and PySpark, data engineering, and strong governance practices within enterprise risk management.

You will collaborate with model owners and cross-functional teams to translate requirements into scalable solutions, oversee testing, and contribute to policy compliance and documentation.

Qualifications

• Bachelors in quantitative field; advanced degree preferred.
• Strong Python programming and production code experience.
• Experience with quantitative analytics, model onboarding, and monitoring.
• Knowledge of model risk, data privacy, and governance requirements.

Responsibilities

• Design, develop, implement, and govern quantitative analytics and AI-enabled automation for CECL, CCAR, and Model Monitoring.
• Develop modular, production-ready Python and PySpark code and data pipelines with strong version control and testing.
• Support model onboarding, monitoring, and remediation with rigorous testing and documentation.
• Diagnose and resolve data quality, workflow, and model execution issues across large datasets.

Skills

Analytical thinking

Credit risks

Data analytics

Financial analysis

Model development

Operational risks

Quantitative models

Risk appetite

Education

Bachelors

Tools

PySpark

SQL

Git/Bitbucket

APIs

Parquet/CSV

Job description

Quantitative Analytics & Model Analyst Senior - Credit Loss Forecasting (CLF)### Quantitative Analytics & Model Analyst Senior - Credit Loss Forecasting (CLF)Apply: PA - Pittsburgh (15222): VA - Tysons Corner: NJ - East Brunswick: DC - Washington (20006): NC - Charlotte (28210): Full time: Posted Today: R240218# **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, OH; Tyson's Corner, VA; Washington, DC; East Brunswick, NJ; or Charlotte, NC. Job Summary: The Quantitative Analytics & Model Analyst Senior is responsible for contributing to the design, development, implementation, and governance of quantitative analytics, model implementation, and AI-enabled automation supporting CECL, CCAR, Model Monitoring, and other strategic risk initiatives. This role requires strong Python software-development skills, solid quantitative and data-engineering capabilities, and experience delivering reliable analytical solutions in enterprise environments. The successful candidate will contribute hands-on across the solution lifecycle, translate business and risk requirements into scalable capabilities, apply sound controls and testing standards, and partner with stakeholders across modeling, technology, validation, risk, and business teams. The role will also help evaluate and introduce machine learning and generative AI capabilities where they provide clear business value and can be implemented with appropriate security, explainability, governance, and human oversight. Key Responsibilities: • Contribute to the design, development, implementation, and enhancement of quantitative analytics, model-support, and AI-enabled automation solutions for CECL, CCAR, Model Monitoring, and other regulatory or business-critical initiatives, providing hands-on support from requirements and design through controlled deployment and production support. • Develop and review modular, testable, production-ready Python and PySpark code, data pipelines, controls, and workflow automation, applying established standards for code quality, version control, testing, documentation, security, and change management. • Support model onboarding, implementation, monitoring, and remediation, including developing and executing unit, integration, regression, reconciliation, and performance testing to confirm implementation accuracy and operational readiness. • Diagnose and resolve issues involving model execution, data quality, workflow orchestration, configuration, and analytical outputs; analyze large, complex datasets to assess model performance and investigate discrepancies, escalating complex issues as appropriate. • Evaluate and apply generative AI, and LLM-based capabilities where appropriate to improve analytics, model operations, monitoring, and documentation, with appropriate testing, security, human oversight, and governance controls. • Support model and analytical governance, including risk assessments, validation support, audit and regulatory responses, and issue remediation, and prepare clear, supportable technical and governance documentation. • Partner with model owners, development, validation, technology, and business teams; participate in design and code reviews; and communicate findings and recommendations clearly to technical and non-technical stakeholders. Required Qualifications: • Bachelor's or Master's degree in Quantitative Finance, Statistics, Mathematics, Computer Science, Data Science, Engineering, Operations Research, or a related quantitative field; advanced degree preferred. • Solid experience in quantitative analytics, model implementation, model monitoring, or AI/ML solutions in enterprise environments, including onboarding, testing, output validation, production deployment, and issue remediation. • Strong hands-on Python programming experience building modular, testable, production-ready solutions, including automated workflows, data pipelines, controls, and reconciliation processes using large, complex datasets. • Solid knowledge of statistical modeling, machine learning, and quantitative methods. • Demonstrated ability to diagnose and resolve issues involving code, data, workflows, and analytical outputs, applying standards for testing, documentation, version control, and change management. • Understanding of model risk, data privacy, information security, responsible AI, and governance requirements. • Strong communication and collaboration skills, with the ability to manage multiple priorities and explain technical concepts to technical and non-technical audiences. Preferred Qualifications: • Hands-on experience with PySpark, SQL, Git/Bitbucket, APIs, Parquet and CSV data, Slurm or comparable distributed job scheduling, and enterprise model-execution platforms and workflow orchestration. • Experience with quantitative models in financial services, particularly credit risk, CECL, CCAR, stress testing, or model governance, along with knowledge of banking products and regulatory expectations in highly regulated environments. • Experience applying AI/ML or generative AI/LLM-based solutions to analytical or model workflows, including agentic workflows, retrieval-augmented generation, vector databases, evaluation, and guardrails. • Experience participating in design and code reviews and mentoring junior team members.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. Listed below are skills, competencies, work experience, education, and required certifications/licensures needed to be successful in this position.## **Preferred Skills**Analytical Thinking, Credit Risks, Data Analytics, Financial Analysis, Model Development, Operational Risks, Quantitative Models, Risk Appetite## **Competencies**Bank Quantitative Analysis, Consulting, Data Gathering and Reporting, Effective Communications, Predictive Analytics, Quantitative Techniques, Regulatory Environment - Financial Services, Testing## **Work Experience**Roles 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.## **Education**Bachelors## **Certifications**No Required Certification(s)## **Licenses**No Required License(s)## **Language Assessments**No Required or Preferred Language Assessments# **Pay Transparency**Base Salary: $86,250.00 – $172,500.00Salaries 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 11/06/2026, 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 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.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 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.To learn more about these and other programs, including benefits for full time and part-time employees, visit pncthrive.com.