Data Scientist – Corporate & Institutional Banking

Role Overview

As a Data Scientist within PNC’s Corporate and Institutional Banking (C&IB) organization, 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.

What You Will Do

Key responsibilities include using Python or R to explore data, perform analysis, and rapidly prototype analytical approaches within repeatable workflows, designing, developing, validating, and monitoring interpretable machine learning models, and owning the end-to-end delivery of analytical solutions.

Why It Might Be a Fit

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.

Requirements

• 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
• 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

Benefits

• Medical/prescription drug coverage (with a Health Savings Account feature)
• Dental and vision options
• Employee and spouse/child life insurance
• Short and long-term disability protection
• 401(k) with PNC match
• Pension and stock purchase plans
• Dependent care reimbursement account
• Back-up child/elder care
• Adoption, surrogacy, and doula reimbursement
• Educational assistance
• Wellness program with financial incentives
• Maternity and/or parental leave
• Up to 11 paid holidays each year
• 9 occasional absence days each year
• Between 15 to 25 vacation days each year
• Years of service

Tagged as: Data Analysis, Python, SQL