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PNC

Senior Quantitative Analytics & Model Analyst – C&IB – Commercial

PNC

Senior Quantitative Analyst at PNC developing quantitative and machine learning models for decision support. Collaborating with teams to analyze data and deliver insights for business solutions.

Posted 6/3/2026full-timePittsburgh • Ohio, Pennsylvania, Virginia • 🇺🇸 United StatesSenior💰 $86,250 - $172,500 per yearWebsite

Tech Stack

Tools & technologies
PySparkPython

About the role

Key responsibilities & impact
  • Develop, implement, and maintain quantitative and machine learning models for analytics and decision support.
  • Apply statistical and mathematical techniques, including logistic and linear regression, to solve business problems.
  • Perform data analysis, feature engineering, model training, testing, and validation.
  • Use Python to write clean, efficient, and well documented code for modeling and analysis.
  • Evaluate model performance using appropriate metrics and ensure robustness and accuracy.
  • Prepare presentations and written documentation to clearly communicate model methodology, results, and insights to technical and non technical audiences.
  • Collaborate with cross functional partners to understand requirements and translate them into analytical solutions.
  • Support model lifecycle activities, including enhancements, recalibration, and monitoring.

Requirements

What you’ll need
  • 2–3+ years of professional experience in quantitative analytics, modeling, or a related role
  • Strong Python programming and coding skills
  • Solid foundation in mathematics and statistics
  • Hands on experience with logistic regression and linear regression
  • Experience applying machine learning techniques
  • Proven experience developing and implementing models end to end
  • Ability to build or demonstrate a portfolio of modeling or analytical work
  • Bachelor’s degree in mathematics, Statistics, Quantitative Analytics, or a related quantitative field
  • Strong presentation, communication, and documentation skills, with the ability to explain complex concepts clearly.
  • Preferred: Experience with PySpark or working in distributed data environments
  • Preferred: Banking or financial services experience
  • Preferred: Knowledge of credit risk or portfolio metrics such as PD (Probability of Default), LGD (Loss Given Default), and EAD/ED (Exposure at Default)

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
  • paid time off, including 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, depending on career level; and years of service

ATS Keywords

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Hard Skills & Tools
quantitative analyticsmachine learningstatistical techniquesmathematical techniqueslogistic regressionlinear regressiondata analysisfeature engineeringmodel trainingmodel validation
Soft Skills
presentation skillscommunication skillsdocumentation skillscollaborationproblem-solving