Data Scientist – Corporate & Institutional Banking

PNC

Data Scientist developing analytical solutions for Corporate and Institutional Banking at PNC. Collaborating with cross-functional teams to address complex business problems using machine learning and data analysis.

Posted 6/3/2026full-timePittsburgh • Alabama, North Carolina, Ohio, Pennsylvania, Texas • 🇺🇸 United StatesJuniorMid-Level💰 $86,250 - $172,500 per yearWebsite

Tech Stack

Tools & technologies

ApacheFlaskPySparkPythonSparkSQL

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.
Experience developing and evaluating traditional ML models, including feature engineering and performance assessment.
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.
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.

Benefits

Comp & perks

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
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

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

PythonRSQLApache SparkPySparksparklyrSpark SQLmachine learningfeature engineeringGenAI

Soft Skills

communicationcollaborationrequirement gatheringdocumentationperformance trackingcross-domain expertiseproblem-solvinganalytical thinkingadaptabilityteamwork