Data Scientist - Corporate & Institutional Banking

Data ScientistAt 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 Data Scientist within PNC's Corporate and Institutional Banking (C&IB) organization, you will be based in Pittsburgh or Philadelphia, PA, Cleveland, OH, Birmingham, AL, Wilmington, DE, Charlotte, NC, or Houston, TX.Job Summary: PNC is seeking a Data Scientist to join the Corporate and Institutional Banking (C&IB) team. In this role, you will work closely with business stakeholders, product managers, and engineering teams to explore data, develop interpretable machine learning and analytical solutions, and deliver those solutions into production to address complex business problems and support C&IB's growth objectives. The team's work spans key business verticals including Sales, Credit and Underwriting, and Operations, providing opportunities to apply analytics across the full lifecycle of client engagement, risk decisioning, and operational execution.The ideal candidate combines strong analytical problem solving skills with practical experience in data analysis, machine learning, and Generative AI, and is able to clearly communicate insights and translate business needs into scalable, production ready analytical solutions and data products.Key Responsibilities:Use Python or R to explore data, perform analysis, and rapidly prototype analytical approaches within repeatable workflows.Design, develop, validate, and monitor interpretable machine learning models using sound statistical and modeling techniques.Own the end-to-end delivery of analytical solutions—from prototype through testing, validation, and scalable production deployment—collaborating closely with engineering and testing partners to ensure production readiness.Act as a key communication bridge across business, product, and engineering teams to gather and document requirements, clearly communicate analytical solutions, and ensure business needs are accurately implemented.Define and track performance metrics to measure solution effectiveness and business impact.Required Experience & Skills:2–3 years of relevant, post-graduate professional experience as a Data Scientist or in a comparable analytics role.Ability to design and develop interactive dashboards to communicate, visualize, and monitor analytical results using Python or R–based frameworks (e.g. R Shiny, Dash, Flask)Strong programming experience in Python or R.Strong SQL skills and experience working with large datasets.Experience working with Apache Spark using one or more languages (e.g. PySpark, sparklyr, or Spark SQL).Experience with Git or comparable version control tools.Machine Learning: Experience developing and evaluating traditional ML models, including feature engineering and performance assessment.Generative AI: Experience building applied GenAI solutions, including familiarity with retrieval augmented generation and related architectural approaches.Experience producing delivery artifacts such as business requirements, user stories, and test cases.Experience supporting testing, validation, and transitions from analytical prototype to production.Master's degree in quantitative fields (Computer Science, Data Science, Machine Learning, Mathematics, Statistics), or Bachelor's degree with equivalent practical experience.