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 an Associate Data Scientist within PNC's Balance Sheet Analytics & Modeling Marketing & Customer Analytics organization, you will be based in you will be based in Pittsburgh or Philadelphia, PA, Cleveland, OH, Charlotte, NC, Wilmington, DE, Dallas or Houston, TX and Tysons, VA. This position is primarily based in a PNC location. Responsibilities require time in the office or in the field on a regular basis.

Our marketing team is at the forefront of this mission, leveraging data to create personalized and effective campaigns that drive customer engagement and business growth. We are seeking a skilled and passionate Associate Data Scientist to join our team and build the data infrastructure that powers our marketing intelligence.

Job Responsibilities:

As an Associate Data Scientist for the Marketing and Customer Analytics Data Enablement team, you will be a key player in building and maintaining the data pipelines that enable our marketing team to make data-driven decisions. You will work closely with marketing analysts, data scientists, and business stakeholders to understand their data needs and translate them into robust, scalable, and reliable data solutions. Your work will directly impact our ability to understand customer behavior, optimize campaign performance, and personalize our communication.

Job Duties:

• Design & Development: Build, test, and maintain robust data pipelines and ETL/ELT processes to ingest, transform, and load data from various sources (e.g., customer databases, marketing platforms, digital channels, third-party data providers) into our data warehouse.
• Data Modeling: Collaborate with marketing and analytics teams to design and implement efficient data models that support reporting, ad-hoc analysis, and machine learning initiatives.
• Infrastructure Management: Help design, manage and optimize our data infrastructure, including data warehouses, data lakes, and data orchestration tools (e.g., Airflow).
• Data Quality & Governance: Implement processes and tools to ensure data accuracy, consistency, and reliability. Monitor data pipelines for issues and proactively resolve them. Establish and maintain data governance best practices within the marketing data ecosystem.
• Performance Optimization: Optimize queries and data structures to improve the performance and efficiency of data access for analysts and data scientists.
• Collaboration: Partner with cross-functional teams, including product, engineering, and compliance, to ensure data is handled securely and in accordance with banking regulations.
• Innovation: Stay current with the latest data engineering technologies and methodologies and propose new solutions to improve our data platform.

Preferred skills and experience:

• 2+ years of experience as a Data Scientist, with a strong preference for experience in a marketing or financial services context.
• Strong proficiency in Python, SQL and Spark is essential.
• Hands-on experience with modern cloud data warehouses like Snowflake, Big Query, or Amazon Redshift.
• Experience building and managing ETL/ELT pipelines using tools like Apache Airflow, or similar technologies.
• Experience with at least one major cloud provider (AWS, or Azure).
• Solid understanding of data modeling principles (e.g., star schema, snowflake schema).
• Excellent problem-solving skills and attention to detail.
• Strong communication and interpersonal skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• A proactive and collaborative attitude, with a passion for building data solutions that deliver real business value.
• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field
• Experience with real-time data streaming technologies (e.g., Kafka, Kinesis).
• Familiarity with marketing platforms and their APIs (e.g., Adobe Analytics, Salesforce Marketing Cloud, Google Ads).
• Knowledge of machine learning concepts and experience building data pipelines for ML models.
• Familiarity with financial industry regulations and data security best practices.

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

Job Description