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/Modeling Consultant Sr. within PNC's Model Risk Management organization, you can be based in Pittsburgh, PA; Tysons Corner, VA; New York City, NY; or Charlotte, NC; or Raleigh, NC.

We are seeking an accomplished Model Validation Expert to be a part of our Model Risk Management team at PNC. The position reports to the Senior Validation Manager for Market Risk and Counterparty Risk Models and is part of the Independent Risk Management organization.

This role involves performing rigorous independent reviews, as well as providing expert oversight, of some of PNC’s most important models, including interest rate models, securities risk analytics models, derivative pricing models, Value at Risk (VaR) models, and counterparty credit risk measurement models, such as Potential Future Exposure (PFE), Credit Valuation Adjustment (CVA), and Funding Valuation Adjustment (FVA).

Key Responsibilities:

1. Independent Model Review: Perform qualitative and quantitative assessments of all aspects of models including data quality and integrity, theoretical assumptions and methodologies, and performance testing; Specific duties include: (i) assess conceptual soundness and performance of models based on detailed model documentation and testing results (ii) perform independent testing of model assumptions (iii) use quantitative tools and techniques to measure and analyze model risks; (iv) evaluate identified model risks and reach conclusions on strengths and limitations of the model; (v) conduct on-going communication with model stakeholders such as developers, owners and reviewers; and (vi) prepare detailed validation reports on quantitative models/tools for internal/external communications and/or regulatory compliance, using applicable templates.

2. Expert Oversight: As the Model Validation Expert, you will provide expert oversight for the models within the assigned subject area(s), providing validators with guidance on the independent review of the models and ensuring that validation work is performed in accordance with the model risk management framework.

3. Stakeholder Collaboration and Communication: Establish effective relationships with key stakeholders, including model owners and model developers. Communicate validation results and insights clearly and concisely to both technical and non-technical audiences, including regulatory staff members. Collaborate within the Model Risk Management team to enhance validation processes and contribute to the continual improvement of market and counterparty risk management practices within the organization.

Qualifications:

- Master's or Ph.D. in a quantitative field such as Finance, Physics, Mathematics, or a related discipline with a stochastic calculus background.
- Experience in market risk and counterparty risk model development and/or validation within the financial services industry is required.
- Knowledge of regulatory requirements related to market and counterparty credit risk models, including PFE, CVA, FVA, derivative pricing models, VaR models.
- Strong communication skills, both written and verbal, with the ability to convey complex technical concepts to diverse stakeholders.
- Hands-on experience with Python, R, MATLAB, SQL, and QuantLib.

Job Description

• Independently performs the most complex quantitative analyses and models development to support decision-making by running quantitative strategies.
• Develops new model frameworks by supporting the line of business. Refines, monitors, and validates existing models. Conducts on-going communication with model owners and model developers during the course of the review. Works with large data to create models.
• Performs the most complex qualitative and quantitative assessments on all aspects of models including theoretical aspects, model design and implementation as well as data quality and integrity. Reviews reports