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 Specialist within PNC's Retail Lending Decision Science organization you will use data and analytics to improve business results and customer outcomes. The candidate will have the opportunity to combine their knowledge of the consumer lending business, operational execution and analytical techniques to craft actionable strategies that drive results in the default lifecycle. The ideal candidate will play a pivotal role in developing, implementing, and refining default strategies to optimize recovery rates, minimize losses, and enhance customer relationships. This role requires a deep understanding of data analytics, risk management, and strategic decision-making. This role will be based in Pittsburgh, Cleveland, Tysons Corner, Wilmington, Houston, Dallas, New York, Birmingham, Charlotte, Atlanta, Austin or Chicago. The 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 the manager’s discretion.

In this role you will:
• Perform Strategic Analysis: Analyze default trends, customer behavior, and economic factors to develop effective default management strategies.
• Define Requirements: Define and communicate technical and functional requirements to stakeholders to ensure accurate and timely delivery of objectives.
• Interpret Data: Utilize advanced analytics tools and methodologies to interpret large datasets, identify patterns, and derive actionable insights.
• Assess Risk: Evaluate the risk associated with default scenarios, including credit risk, operational risk, and market risk, to inform strategic decision-making.
• Collaborate: Work closely with cross-functional teams, including risk management, finance, operations, and legal departments, to ensure alignment and execution of default strategies.
• Monitor Performance: Establish key performance indicators (KPIs) and regularly monitor the effectiveness of default strategies, making data-driven adjustments as necessary.
• Ensure Compliance: Stay abreast of industry regulations, best practices, and emerging trends related to default management to ensure compliance and mitigate regulatory risks.
• Communication with Stakeholders: Present findings, recommendations, and progress updates to senior leadership, stakeholders, and regulatory bodies as required.

Requirements:
• Strong understanding of data mining techniques, curating, processing, and transforming data to produce sound datasets
• Experience in defining, recording, and communicating technical and functional requirements to product, risk, and technology teams.
• Strong project management skills and familiarity with software development lifecycle
• Experience with analytical programming languages, tools, and libraries (Python ecosystem)
• Experience in SQL and relational databases
• Experience in analyzing complex problems and translating them into an analytical approach
• Experience with analytics applied to financial services or consumer lending
• Strong leadership, stakeholder management, communication, partnership, and teamwork skills
• Degree in an analytical field preferred. (e.g., Computer Science, Data Science, Engineering, Applied Mathematics, Data Analysis, Statistics, Operations Research).
• Knowledge of Tableau helpful, but not required.

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