Portfolio Analytics & Strategy Specialist - Credit Portfolio Management

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 Data, Modeling & Analytics Credit Portfolio Management organization, you will be based in Denver, CO.

At a high-level, this role requires an adept understanding of data analytics, risk management, and strategic decision‑making.

• Responsible for developing subject matter expertise for your assigned industries.
• Perform research, analytics and assessment of risks stemming from assigned industries that may impact PNC’s Commercial & Industrial portfolio.
• Responsible for developing risk management and growth strategies based around commercial risk/return metrics.
• Collaborate with cross‑functional teams, including credit risk management, finance, operations, and model development, to ensure alignment and execution of strategic initiatives.
• Support PNC’s C&IB business in the first line as well as credit partners in the second line.
• Leverage python coding (including PySpark), financial reporting, Tableau and foundational understanding of commercial banking and metrics to execute risk analysis.
• Share complex analytical results with non‑technical audiences.
• Provide financial and regulatory reporting and analyses to maintain adequate controls over the financial and regulatory reporting processes.
• Run complex business performance, risk and operational analytics.
• Develop analytical methods/models to assess market, credit and/or operational risk of new and existing financial products.
• Rigorously analyze large datasets to improve risk‑adjusted returns, deliver profitable growth, and communicate conclusions.
• Synthesize analytical results and develop, recommend, and implement business strategies that improve lending decisions, manage risk, increase revenues, reduce exposure to losses, meet business goals, and improve performance.
• Establish baselines for strategies and track actual performance against expectations.
• Apply predictive models, third‑party data, and other tools to develop and execute segmentation and targeting for acquisition and portfolio strategies.
• Manage engagements with internal and external information suppliers to ensure solutions are fit for purpose while maintaining governance and oversight.
• Design, develop and monitor test designs and analytical reporting to track and enhance strategies.
• Design/enhance standard reporting suites for regular product/portfolio reviews.
• Collaborate with finance and risk partners to assess and establish credit risk appetite and understand its implications, establishing policies and procedures governing risk monitoring.

• Experience distilling complex data and feedback into concise, standalone presentations.
• Experience manipulating data and performing analysis in Tableau and Excel.
• Proficiency in data analytics tools including Python (PySpark) and SQL.
• Understanding of the fundamentals of commercial banking and banking products.
• Demonstrated thought leadership and strategic thinking for decision making.
• Exercising initiative and using good judgment to make sound decisions.
• Ability to influence, negotiate, and persuade partners to reach agreeable exchanges and positive outcomes.

Successful candidates must demonstrate appropriate knowledge, skills, and abilities for a role. Requirements:

• University/college degree with 5+ years of industry‑relevant experience.
• Preferred:
  Strong background in analytical thinking, credit risks, data analytics, financial analysis, model development, operational risks, quantitative models, risk appetite, and regulatory environment.
• Experience with analytical approach, banking products, big data management, business analytics, credit risk, mathematics of financial instruments, operational risk, performance measurement, predictive analytics, pricing models and analytics.
• Any relevant…