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 Development Analyst Senior within PNC's Fraud Model Implementation organization, you will be based in Pittsburgh or Philadelphia, PA. This position is primarily based in a PNC location. Responsibilities require time in the office or in the field. 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
• 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)

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 expe