Card Fraud Data Scientist — Risk Analytics

Fairygodboss; Cleveland (OH); On-site; USD 86,000 - 144,000; Full time

Benefits offered by this job

Medical/prescription drug coverage

Dental and vision options

401(k) with PNC match

Pension and stock purchase plans

Health Savings Account feature

Job summary

PNC is seeking a Fraud Data Scientist in Cleveland, OH to lead advanced analytics for credit card portfolios. You will leverage Python, R, and SQL to build predictive models, monitor risk, and influence lending decisions.

This in-office role emphasizes collaboration with cross-functional teams to balance risk with growth and regulatory compliance. The position requires prior card fraud or authorization experience, strong data science skills, and the ability to translate complex analyses into

Qualifications

• Experience with credit/debit card authorization strategies, modeling or monitoring.
• Strong analytical skills and ability to work with large datasets.
• Proficiency in Python (Spark), R, and SQL for data science tasks.

Responsibilities

• Provide financial and regulatory analytics and develop methods to assess risk of financial products.
• Analyze large datasets to improve risk-adjusted returns and communicate insights to stakeholders.
• Develop segmentation and targeting for portfolio strategies using predictive models and third-party data.
• Collaborate with business, credit, data, and model teams to design test designs and reporting.
• Work with Finance and Risk to establish credit risk appetite and governance policies.

Skills

Spark/Python

Data Science & Analytics

Optimization Frameworks

Graph/Linkage Analysis

Data Visualization

Education

Bachelor's degree

Job description

PNC is seeking a Fraud Data Scientist in Cleveland, OH to lead advanced analytics for credit card portfolios. You will leverage Python, R, and SQL to build predictive models, monitor risk, and influence lending decisions.

This in-office role emphasizes collaboration with cross-functional teams to balance risk with growth and regulatory compliance. The position requires prior card fraud or authorization experience, strong data science skills, and the ability to translate complex analyses into