Quantitative Analytics & Model Consultant Senior - C&IB Commercial Real Estate

Quantitative Analytics & Model Consultant Senior

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 Consultant Senior within PNC's C&IB Commercial Real Estate organization, you will be based in Pittsburgh, or Philadelphia, PA; Cleveland, OH; Wilmington, DE; or Houston, TX.

Key Responsibilities:

• Develop, enhance, and maintain loss forecasting models for Commercial Real Estate portfolios, including PD/LGD and expected loss models
• Perform predictive modeling and machine learning/statistical modeling to assess risk drivers, portfolio behavior, and loss outcomes
• Analyze large and complex datasets using Python and PySpark in distributed computing environments
• Design, implement, test, and monitor models in accordance with model risk management and governance standards
• Produce high quality model documentation, including methodology, assumptions, limitations, and performance analysis
• Partner with Commercial Real Estate, Credit Risk, Finance, and Risk Management stakeholders to translate business needs into quantitative solutions
• Support regulatory reviews, audits, and model validation activities
• Present analytical findings and model results to senior leadership, risk committees, and non technical stakeholders
• Contribute to analytics process improvement, automation, and scalability initiatives
• Explore and apply Generative AI (GenAI) or advanced analytics techniques where appropriate to enhance model development and efficiency

Required Experience & Skills:

• 6+ years of professional experience in quantitative analytics, modeling, or risk management within Financial Services

• Strong hands on Python programming and coding experience

• Experience working with PySpark and large scale data processing

• Deep experience in predictive modeling and machine learning/statistical modeling

• Proven experience developing and maintaining loss forecasting models

• Strong statistical and mathematical background

• Demonstrated ability to produce clear, thorough model and technical documentation

• Excellent presentation and communication skills, with the ability to explain complex analytics to business audiences

Preferred Experience & Skills:

• Experience specifically within Commercial Real Estate (CRE) portfolios

• Hands on experience with PD/LGD modeling and loss forecasting

• Master's degree in mathematics, Statistics, Quantitative Finance, Data Science, or a related discipline

• Exposure to Generative AI (GenAI) tools or techniques applied to analytics, modeling, or automation

• Experience working in a highly regulated banking environment

• Strong executive level communication and stakeholder engagement skills