Data Scientist - Corporate & Institutional Banking

PNCPittsburgh, PA
$55,000 - $142,600Onsite

About The Position

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. 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. For nearly 160 years, PNC has strived to make a meaningful impact for our employees, customers, communities, and shareholders. We believe our success and positive reputation are built on open and honest dialogue, an unwavering focus on smart risk management, relationship-based customer service and community investments. Our inclusive workplace allows our employees to be heard, valued, and developed to do their best work. Being a great place to work means we are making a lasting difference for everyone we serve. Check out the top reasons to join PNC. PNC’s total rewards package includes things like time off, benefits, learning and career development, wellness programs, recognition and much more. The benefits and programs highlighted below are just a sampling of what PNC offers its employees. To learn more, visit our Total Rewards page. If you're not ready to apply yet, or you'd like to learn more about PNC, join the Talent Community to receive regular updates on what's happening at PNC and available career opportunities. Click to join! Job Description Performs analytical tasks on vast amounts of structured and unstructured data to extract actionable business insights. Participates in the data gathering, data processing and data mining of large and complex datasets. Develops algorithms using advanced mathematical and statistical techniques like machine learning to predict business outcomes and recommend optimal actions to management. Runs analytical experiments in a methodical manner to find opportunities for product and process optimization. Assists in the presentation of business insights to management using visualization technologies and data storytelling. May partner with Data Architects, Data Analysts, Data Engineers and Visualization Experts to develop data-driven solutions for the business.

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 (e.g. R Shiny, Dash, Flask)
  • Programming: o Strong programming experience in Python or R. o Strong SQL skills and experience working with large datasets. o Experience 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: o Machine Learning: Experience developing and evaluating traditional ML models, including feature engineering and performance assessment. o Generative AI: Experience building applied GenAI solutions, including familiarity with retrieval augmented generation and related architectural approaches.
  • Data Product Delivery: o Experience producing delivery artifacts such as business requirements, user stories, and test cases o Experience supporting testing, validation, and transitions from analytical prototype to production

Nice To Haves

  • Exposure to business domains such as credit, accounting, or financial operations.
  • Familiarity with underwriting concepts or a willingness to learn them on the job.
  • Experience working across multiple business areas or interest in developing cross‑domain expertise.
  • Exposure to entity resolution or record‑linkage problems, including matching, deduplication, or linking entities across disparate internal or external data sources.
  • Master’s degree in quantitative fields (Computer Science, Data Science, Machine Learning, Mathematics, Statistics), or
  • Bachelor’s degree with equivalent practical experience

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.

Benefits

  • PNC offers a comprehensive range of benefits to help meet your needs now and in the future. Depending on your eligibility, options for full-time employees include: 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, including select programs fully paid; a robust wellness program with financial incentives. In addition, PNC generally provides the following paid time off, depending on your eligibility: maternity and/or parental leave; up to 11 paid holidays each year; 9 occasional absence days each year, unless otherwise required by law; between 15 to 25 vacation days each year, depending on career level; and years of service.
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