Data Scientist - Corporate & Institutional Banking

Job : R216795

Posted:

Location:

PA
- Pittsburgh (15222); PNC Bank N.A. (PA375);
Birmingham
- Brock (AL112);
One PNC Plaza (PA370);
Houston Plaza (TX334);
Delaware Avenue Offices (DE023);
Charlotte Piedmont Center (NC037);
Brecksville Lending Services (OH003); PNC Center
- Cleveland (OH001)
Salary: $86,250.00 - $Type:
Full time Country:
United States of America Company: PNCPosition 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 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)
Programming:oStrong programming experience in Python or R.oStrong SQL skills and experience working with large datasets.oExperience working with Apache Spark using one or more languages (e.g. PySpark, sparklyr, or Spark SQL).o

Experience with Git or comparable version control tools.

Model Development:oMachine Learning:
Experience developing and evaluating traditional ML models, including feature engineering and performance assessment.oGenerative AI:
Experience building applied GenAI solutions, including familiarity with retrieval augmented generation and related architectural approaches.

Data Product Delivery:oExperience producing delivery artifacts such as business requirements, user stories, and test…