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 Portfolio Analytics & Strategy Analyst Senior within PNC's Balance Sheet Analytics & Modeling Fraud Model Implementation organization, you will be based in Pittsburgh or Philadelphia, PA, Cleveland, OH, Wilmington, DE, Tysons, VA, New York City, Charlotte, NC, Dallas or Houston, TX. This position is primarily based in a PNC location. Responsibilities require time in the office or in the field on a regular basis. Some responsibilities may be performed remotely, at manager's discretion.

This position is responsible for developing, implementing, and maintaining of Fraud Models that support our retail and commercial businesses. This position requires experience and knowledge of: Financial Crimes; machine learning applications and their explainability; big data structuring and computation; and process optimization. You will work closely with our business partners across different lines of business (Retail, commercial, Technology, Security, and Enterprise Fraud); business process/model owners; and independent risk management, and audit. You will frequently be required to present your work to peers, senior PNC executives and regulators.

Preferred experience:

• Solid experience in coding with Python/R—specifically, PySpark or other “big data” applications.
• Excellent written and communication skills, both in technical and nontechnical [communications]
• Problem solving skills and ad hoc analyses
• Ability to work under tight timelines
• Being a collaborative team player
• A self-starter with an innate curiosity for how/why things work
• A desire to learn and knowledge of continuous improvement/optimization
• PhD or Masters in a quantitative field
• Relevant experience in at least one area of Banking/Financial Services / Consulting / Technology
• Experienced in Fraud/Financial Crimes/Anti-money laundering detection and prevention
• Experienced with Machine Learning models – deep learning, large language models, and graph data base
• Model Development Lifecycle (development to validation to implementation to production and repeat

PNC will not provide sponsorship for employment visas or participate in STEM OPT for this position.

Job Description

• Provides financial and regulatory reporting and analyses to maintain adequate controls over the financial and regulatory reporting processes. Responsible for running complex business performance, risk and operational analytics. May include the development of analytical methods/models to assess market, credit and/or operational risk of new and existing financial products.
• Leverages business / product expertise to rigorously analyze large datasets, improve risk adjusted returns, deliver profitable growth, and communicate conclusions. Synthesizes analytical results and develops, recommends, and implements business strategies that improve lending decisions, assist in managing risk, increase revenues, reduce exposure to losses, meet business goals, and improve performance. Establishes baselines for strategies and tracks actual performance to expectations.
• Applies predictive models, third party data, and other tools to develop and execute appropriate segmentation and targeting for acquisition and portfolio strategies to provide insight into portfolio risk. Manages engagements with internal and external information suppliers ensuring solution is fit for purpose while maintaining appropriate governance and oversight.
• Works with business, credit, data, and model development partners to design, develop, and monitor test designs and analytical reporting to track and enhance strategies. Designs / enhances standard reporting suites for regular product / portfolio reviews.
• Collaborates with the line of business, Finance, and Risk partners to assess and establish credit risk appetite and to understand its implications, as wel