Portfolio Analytics & Strategy Specialist (Card Fraud Strategy)

PNC•Columbus, OH

1d•$91,000 - $169,000•Onsite

About The Position

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.

Requirements

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.
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.
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)
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
Bachelors

Nice To Haves

experience with R is a plus
Experience with graph analysis, linkage analysis, network analysis, or entity relationship analysis.
Experience leveraging Apache Spark for large-scale data processing and analytics.

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.

Benefits

medical/prescription drug coverage (with a Health Savings Account feature)
dental and vision options
employee and spouse/child life insurance
short and long-term disability protection
401(k) with PNC match
pension and stock purchase plans
dependent care reimbursement account
back-up child/elder care
adoption, surrogacy, and doula reimbursement
educational assistance, including select programs fully paid
a robust wellness program with financial incentives
maternity and/or parental leave
up to 11 paid holidays each year
9 occasional absence days each year, unless otherwise required by law
between 15 to 25 vacation days each year, depending on career level; and years of service