Portfolio Analytics & Strategy Specialist (Card Fraud Strategy)

PNC Financial Services Group, Inc.; Columbus (OH); On-site; USD 91,000 - 169,000; Full time

Job summary

PNC Financial Services Group, Inc. is seeking a Fraud Data Scientist (Credit/Debit Card) to advance analytics and strategy across fraud prevention initiatives.

You will lead complex analyses of card fraud patterns, develop data-driven countermeasures, and partner with cross-functional teams to balance risk and customer experience. The role emphasizes senior technical mentorship, data visualization, and communication of findings to executives in a fast-paced, in-office environment across multiple

Qualifications

• 5+ years in Data Science, Analytics, Fraud Analytics, Risk Analytics, or related field.
• 1+ year fraud analytics, fraud strategy, or fraud risk management experience.
• Strong Python experience for analytics; R is a plus.
• Advanced proficiency with SQL for querying large datasets.
• Experience with large-scale datasets and analytical environments.

Responsibilities

• Lead analytical initiatives focused on Credit Card and Debit Card fraud prevention.
• Analyze large volumes of structured and unstructured data to identify patterns and trends.
• Develop data-driven recommendations balancing fraud loss, customer experience, and growth.
• Design, evaluate, and optimize fraud rules, detection strategies, and monitoring frameworks.
• Apply statistical modeling, predictive analytics, data mining, and quantitative analysis to fraud risk management.
• Perform graph/ linkage analysis to uncover fraud networks.
• Collaborate across Fraud, Operations, Technology, Product, Modeling, Legal, and other teams.
• Present findings and strategy recommendations to management and senior leaders.
• Translate analytics into actionable business insights for technical and non-technical stakeholders.
• Mentor junior analysts and contribute to analytic framework development.
• Support development of fraud monitoring capabilities and reporting methodologies.

Skills

Data Science

Fraud Analytics

Python

SQL

Apache Spark

Graph analysis

Data Visualization

Education

Bachelor's degree

Tools

Apache Spark

Power BI

SQL

Job description

Job Profile

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 Fraud Data Scientist (Credit/Debit Card Transaction & Strategy) within PNC's Enterprise Fraud organization, you can be based in Birmingham, AL; Phoenix, AZ; Lakewood, CO; Strongsville, OH; Columbus, OH; Philadelphia, PA; Pittsburgh, PA; Dallas, TX.

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

We are seeking a Portfolio Analytics & Strategy Specialist to join our Fraud Strategy & Analytics team, supporting both Credit Card and Debit Card fraud mitigation initiatives.

As a senior member of the team, you will play a key role in developing and optimizing fraud prevention strategies that balance fraud loss reduction, customer experience, and business growth. You will analyze large and complex datasets, identify emerging fraud trends, recommend strategic countermeasures, and partner closely with cross-functional stakeholders across Product, Technology, Operations, Modeling, and Fraud Risk teams.

Core Responsibilities

• Lead complex analytical initiatives focused on Credit Card and Debit Card fraud prevention and fraud mitigation strategies.
• Analyze large volumes of structured and unstructured data to identify fraud patterns, emerging threats, behavioral trends, and opportunities for optimization.
• Develop data-driven recommendations that balance fraud loss prevention with customer experience and business growth objectives.
• Design, evaluate, and optimize fraud rules, detection strategies, and monitor frameworks.
• Apply statistical modeling, predictive analytics, data mining, and advanced analytical techniques to support fraud decisioning and risk management efforts.
• Perform graph analysis, linkage analysis, data correlation, and visualization to uncover fraud networks and relationships.
• Collaborate with partners across Fraud, Operations, Technology, Product, Modeling, Legal, and other business functions to drive enterprise-wide solutions.
• Present findings, strategy recommendations, and performance results to management and senior leadership audiences.
• Translate complex analytical findings into actionable business insights for both technical and non-technical stakeholders.
• Support strategic initiatives by evaluating the downstream impact of fraud strategy changes on customers, operations, and business outcomes.
• Act as a senior team member and technical mentor, providing guidance and support to junior analysts.
• Participate in the development and enhancement of analytical frameworks, reporting methodologies, and fraud monitoring capabilities.
• Work in a fast-paced environment where timely analysis and decision-making directly impact business performance and fraud exposure.

Preferred Skills & Experience

• 5+ years of experience in Data Science, Business Analytics, Data Analytics, Fraud Analytics, Risk Analytics, Decision Science, or a related analytical field.
• 1+ year of experience supporting Credit Card or Debit Card fraud analytics, fraud strategy, or fraud risk management.
• Strong programming experience with Python for analytics, statistical analysis, predictive modeling, and data processing; experience with R is a plus.
• Advanced proficiency with SQL for querying, analyzing, and manipulating large datasets.
• Experience working with large-scale datasets and complex analytical environments.
• Strong background in statistical modeling, predictive analytics, data mining, and quantitative analysis.
• Experience leveraging Apache Spark for large-scale data processing and analytics.
• Knowledge of optimization frameworks and analytical techniques used to improve business outcomes.
• Experience with graph analysis, linkage analysis, network analysis, or entity relationship analysis.
• Strong data visualization and storytelling capabilities utilizing tools such as Microsoft Power BI or similar visualization platforms.
• Demonstrated ability to present analytical findings, recommendations, and business impacts to managers, directors, and senior leaders.
• Experience mentoring or providing technical guidance to junior analysts.
• Experience contributing to authorization strategy, fraud detection strategy, fraud monitoring, or fraud loss mitigation programs.
• Background working with Credit Card or Debit Card issuers, Consumer Banking organizations, Credit Unions, Payment companies, or Financial Services institutions.
• Experience partnering with external fraud vendors and third-party solution providers.
• Familiarity with card transaction ecosystems, payment processing, and fraud prevention technologies.
• Prior experience within large-scale card issuer environments such as national banks, card services organizations, or enterprise fraud organizations.

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 experience, education, and required certifications/licensures needed to be successful in this position.

Preferred Skills

Analytical Thinking, Credit Risks, Data Analytics, Financial Analysis, Model Development, Operational Risks, Python (Programming Language), Quantitative Models, Risk Appetite, Statistical Models, Structured Query Language (SQL)

Competencies

Analytical Approach, Banking Products, Big Data Management and Analytics, Business Analytics, Credit Risk, Mathematics of Financial Instruments, Operational Risk, Performance Measurement, Predictive Analytics, Pricing Models and Analytics, Regulatory Environment - Financial Services, Risk Management Banking

Work Experience

Roles at this level typically require a university / college degree, with 5+ years of industry-relevant experience. Specific certifications are often required. In lieu of a degree, a comparable combination of education, job specific certification(s), and experience (including military service) may be considered.

Education

Bachelors

Certifications

No Required Certification(s)

Licenses

No Required License(s)

Language Assessments

No Required or Preferred Language Assessments

Pay Transparency

Base Salary: $91,000.00 - $169,000.00

Salaries may vary based on geographic location, market data and on individual skills, experience, and education. This role is incentive eligible with the payment based upon company, business and/or individual performance.

Application Window

Generally, this opening is expected to be posted for two business days from 07/19/2026, although it may be longer with business discretion