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 Digital Fraud Data Scientist within PNC's Enterprise Fraud - Adapt organization, you will be based in Pittsburgh, PA, Dallas, TX or Birmingham, AL. The position is primarily based in a PNC location. Responsibilities require time in the office or in the field on a regular basis. Some responsibilities may be performed remotely, at the manager’s discretion.

The analyst will assist with analytics when an anomaly or fraud incident within the Digital payments domain (Zelle, Wire, ACH, etc.) reaches the Adapt team. Specific duties to include identifying and understanding fraud patterns, proposing rules and other supplementary countermeasures to address the attack vector, to assess the effectiveness (capture rate) and impact (false positives) of said proposals, present findings to leadership/management, and assess the effectiveness of the implementation post-production compared to the prior expectations. Collaborate with partners in the line of business, monitoring (React), business as usual (Act), and systems (Plan) areas within the Enterprise Fraud Organization, operations, incident management, and other stakeholders to stay ahead of emerging fraud trends. Rapid pace environment due to the nature of the underlying work and the amount of money that can be lost as a window remains open and more bad actors are attracted to exploit it.

Skillsets include usage of statistical and advanced quantitative techniques, transactional behavior analysis, and real-time signals to design and optimize fraud detection rules that enhance customer protection while minimizing friction.

Key Responsibilities:
· Develop, write, and optimize real-time fraud detection rules using data-driven insights
· Analyze large datasets (transactional, behavioral, and device-level) to identify patterns of fraud and abuse
· Leverage statistical, machine learning, ana anomaly detection techniques to support rules-based countermeasures
· Conduct impact analysis and performance monitoring of fraud rules and adjust strategies accordingly
· Partner with fraud operations, digital product teams, and tech to deploy, test, and validate rules in production
· Evaluate and respond to emerging fraud vectors in digital channels
· Translate business problems into analytical solutions with focus on actionable outcomes
· Create dashboards and reports to track fraud trends, rule effectiveness, and key performance metrics

Preferred Skills:
· Ability to approach complex business problems with analytical rigor
· Proficiency in SQL, Python, PySpark, R and/or SAS for data analysis and rule simulation
· Familiarity with big data technologies like Hadoop, Spark, Hive, Impala etc.

Job Description

• Performs analytical tasks on vast amounts of structured and unstructured data to extract actionable business insights.
• Participates in the data gathering, data processing and data mining of large and complex datasets.
• Develops algorithms using advanced mathematical and statistical techniques like machine learning to predict business outcomes and recommend optimal actions to management.
• Runs analytical experiments in a methodical manner to find opportunities for product and process optimization. Assists in the presentation of business insights to management using visualization technologies and data storytelling.
• May partner with Data Architects, Data Analysts, Data Engineers and Visualization Experts to develop data-driven solutions for the business.

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