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 Senior Data Scientist within PNC's Marketing & Customer Analytics organization, you will be based in Pittsburgh, PA, Wilmington, DE or Tysons Corner, VA. This position is primarily based in a PNC location. Responsibilities require time in the office or in the field on a regular basis.

Job Summary:

We are seeking a Senior Data Scientist to join our Marketing and Customer Analytics Modeling team. This role focuses on developing and deploying predictive models that drive targeted marketing strategies, optimize customer acquisition, and enhance portfolio performance. The ideal candidate combines expertise in statistical modeling and machine learning with business acumen to deliver practical modeling solutions for marketing.

Key Responsibilities:

• Collaborate with business partners to design, build, and validate predictive models in the credit card and consumer lending marketing domain using advanced statistical modeling and machine learning techniques.
• Analyze large datasets to uncover insights, create meaningful features, and ensure data quality and relevance for modeling.
• Present analytical findings and actionable insights to senior-level executives in a clear, compelling, and business-focused manner to support strategic decision-making
• Track model performance over time, recalibrate as needed, and communicate results and implications to stakeholders.
• Maintain thorough documentation of modeling processes, assumptions, and validation results to support compliance and model governance requirements.

Preferred Skills and Experience:

• Substantial experience applying statistical modeling and machine learning techniques within financial services; preferably in the credit card and/or consumer lending marketing domain.
• Proficiency in Python, R and SQL. Knowledge of cloud platforms and big data technologies (Spark, Hadoop).
• Excellent communication skills with the ability to explain complex approaches to non-technical stakeholders.
• Understanding of marketing analytics, campaign measurement, targeting strategies, and experimental design.
• Strong attention to detail.

PNC will not provide sponsorship for employment visas or participate in STEM OPT for this position.

Job Description

• Leads the implementation of analytical projects that leverage vast amounts of structured and unstructured data to extract actionable business insights.
• Directs the data gathering, data processing and data mining of large and complex datasets.
• Leads the development of algorithms using advanced mathematical and statistical techniques like machine learning to predict business outcomes and recommend optimal actions to management.
• Leads analytical experiments in a methodical manner to find opportunities for product and process optimization. Presents business insights to management using visualization technologies and data storytelling.
• Partners 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 - 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