LOB Consumer Credit Risk Advisor - Data, Modeling & Analytics

** 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 an LOB Consumer Credit Risk Advisor within PNC's Data, Modeling & Analytics Decisioning Quality Assurance organization, you will be based in Pittsburgh, PA, Cleveland or Brecksville, OH, Tysons Corner, VA, Charlotte, NC or Birmingham, AL.

Role Overview

As a LOB Consumer Credit Risk Advisor, you will support delivery of QA oversight across the full credit lifecycle, including originations, account management, and default management. This role is responsible for evaluating decision quality, identifying risk, and delivering insights that strengthen credit processes and regulatory alignment.

You will serve as a trusted advisor, delivering timely, actionable, and business-focused insights with best-in-class quality. Success in this role requires strong analytical capability, attention to detail, and a client-first mindset.

Key Responsibilities:

- Create curated data sets necessary to execute exams across all credit life cycles.

- Conduct QA reviews across credit lifecycle processes to assess adherence to policy, underwriting standards, and regulatory requirements.

- Identify defects, control gaps, and risks impacting decision accuracy and customer outcomes.

- Document findings with clear, concise, and audit-ready support.

- Understand and execute against Retail Level priorities.

- Analyze QA results to identify trends, root causes, and emerging risks.

- Partner with cross-functional teams (Product, Decision Infrastructure, Operations, Risk) to support QA priorities and remediation efforts.

- Compose and present final reports to business partners.

Preferred skills and experience:

- Bachelor's degree in finance, accounting, business, economics, mathematics, engineering, or equivalent work experience.

- Able to gather and store large data sets using Spark based SQL queries within a Python environment (Jupyter Hub).

- Capable of navigating the full PNC and client ecosystem with agility and insight, including credit and risk frameworks, regulatory expectations, product features, client experience, market trends, and data within PNC systems. The analyst must connect these areas to deliver holistic, business-relevant insights.

- Understanding of credit underwriting concepts (income, housing, DTI, policy rules).

- Strong attention to detail, analytical and problem-solving skills.

- Experience in QA, audit, financial services consulting, credit risk, lending operations, large data analysis, or related field.

- Proficiency in communicating insights and findings clearly in a professional format.

- Desire to grow professionally in a collaborative environment, receive coaching and feedback, and ultimately lead exams.

PNC is an in-office company that fosters a supportive culture where employees can thrive and achieve balance. We encourage candidates to connect with their recruiter and hiring manager to understand workplace expectations and ensure the role aligns with their goals.

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

** Job Description*
* + Reviews activities associated with applicable business segment, including the credit approval process, policy and procedural compliance and portfolio risk management, credit monitoring, and reporting.

+ Maintains in depth knowledge of consumer credit policy and ensures adherence to policy. Deploys appropriate monitoring mechanisms of early performance to manage expected outcomes.

+ Monitors credit by leveraging relevant reporting and assessing trends to identify risk incidences, requests ad - hoc analytics, oversees follow-up, and analyzes output to inform decision - making.

+ Manages and updates credit transaction models utilized within defined asset class and activity and ensures adherence to model management processes (i.e., model validation, testing,…