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

ATS Keywords

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Hard Skills

quantitative analyticsmachine learningstatistical techniquesmathematical techniqueslogistic regressionlinear regressiondata analysisfeature engineeringmodel trainingmodel validation

Soft Skills

presentation skillscommunication skillsdocumentation skillscollaborationproblem-solving

Tools & Technologies

PythonPySpark

Industry Keywords

bankingfinancial servicescredit riskportfolio metricsProbability of DefaultLoss Given DefaultExposure at Default

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