Emerging Fraud Risk Lead — Data Science Expert

PNC; Pittsburgh (Allegheny County); On-site; USD 133,000 - 218,000; Full time

Benefits offered by this job

Medical coverage

401(k) match

Stock purchase plan

Paid time off

Job summary

PNC is seeking a Data Science Expert - Emerging Fraud Risk Lead to identify and mitigate evolving fraud threats across credit card and lending products. You will bridge Fraud Monitoring, Incident Response, and Strategy teams, applying advanced analytics and ML to drive risk reduction.

You will partner with multidisciplinary teams to design detection strategies, validate models, and lead end-to-end analytic initiatives using large-scale data, with strong focus on governance and impact.

Qualifications

• Experience in fraud analytics, data science, machine learning, or risk management, preferably in financial services.
• Advanced experience using SQL, Python, and data science libraries for fraud detection and risk management.
• Hands-on experience developing, testing, and validating ML models (Scikit-learn, XGBoost, LightGBM).
• Strong background in statistics, experimentation, and model validation.

Responsibilities

• Establish and mature the Emerging Fraud Risk capability with scalable detection pipelines.
• Identify emerging fraud threats in Credit Card and Lending products.
• Apply ML and analytics to uncover evolving fraud risks and validate hypotheses.
• Lead investigations translating findings into actionable risk controls.

Skills

Fraud analytics

Data science

Machine learning

PySpark

Python

SQL

Statistics

Anomaly detection

Education

Masters

Tools

Spark/PySpark

Scikit-learn

XGBoost

LightGBM

Pandas

NumPy

Job description

PNC is seeking a Data Science Expert - Emerging Fraud Risk Lead to identify and mitigate evolving fraud threats across credit card and lending products. You will bridge Fraud Monitoring, Incident Response, and Strategy teams, applying advanced analytics and ML to drive risk reduction.

You will partner with multidisciplinary teams to design detection strategies, validate models, and lead end-to-end analytic initiatives using large-scale data, with strong focus on governance and impact.