Senior Quantitative Analytics & Model Analyst – Credit Loss Forecasting

PNC

. Support development, implementation, monitoring, and governance of quantitative models and analytical processes for CECL, CCAR, and Model Monitoring initiatives .

Posted 10/9/2026full-timeUnited StatesSenior💰 $86,250 - $172,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Python programming and quantitative analysis, with a strong focus on developing and optimizing analytical processes and models within financial services. Proficient in collaborating with cross-functional teams to communicate findings and support model governance and regulatory compliance.

Highest-signal resume keywords

Python ProgrammingQuantitative AnalysisModel GovernanceData Pipeline OptimizationMachine Learning

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Hard Skills

Quantitative FinanceStatisticsData ScienceAnalytical WorkflowsAutomated SolutionsData ManipulationModel DevelopmentModel MonitoringRegulatory CompliancePredictive Modeling

Soft Skills

Problem-SolvingCommunicationCollaboration

Tools & Technologies

PySparkGitBitbucketCloud ComputingDistributed Computing

Industry Keywords

CECLCCARStress TestingCredit RiskRegulatory ReportingFinancial ServicesBanking Products

Tech Stack

Tools & technologies

CloudPySparkPython

About the role

Key responsibilities & impact

Support development, implementation, monitoring, and governance of quantitative models and analytical processes for CECL, CCAR, and Model Monitoring initiatives
Develop, maintain, and enhance analytical processes, controls, and supporting infrastructure
Collaborate with model development and validation teams on implementation, onboarding, testing, monitoring, and production deployment
Design, develop, and maintain Python-based solutions for data processing, analytics workflows, controls, and reporting automation
Troubleshoot technical issues involving model execution, data quality, workflow orchestration, and analytical outputs
Perform quantitative analysis on large and complex datasets to identify trends, validate model performance, and support business decisions
Implement and optimize data pipelines using modern analytics and distributed computing frameworks
Apply AI, machine learning, and advanced analytical techniques to improve process efficiency, model monitoring, and analytical insights
Support model governance through documentation, testing, validation, issue remediation, control execution, and audit/regulatory inquiries
Partner with modeling, technology, business, and cross-functional teams
Communicate analytical findings, technical issues, and recommendations to technical and non-technical stakeholders
Independently perform advanced quantitative analyses and model development
Analyze and develop model frameworks; refine, monitor, and review existing models
Conduct qualitative and quantitative assessments of model theory, design, implementation, data quality, and integrity
Measure and analyze model risks, identifying model strengths and limitations
Prepare and analyze documents for validation and regulatory compliance

Requirements

What you’ll need

Bachelor's or Master's degree in Quantitative Finance, Statistics, Mathematics, Computer Science, Data Science, Engineering, or a related quantitative field
Strong Python programming and software development experience
Experience working with large-scale datasets and data manipulation frameworks
Strong problem-solving skills to diagnose and resolve complex analytical and technical issues
Experience developing automated solutions and analytical workflows
Strong communication and collaboration skills
3+ years of relevant/direct industry experience typically required
Comparable combination of education, job-specific certification(s), and experience, including military service, may be considered in lieu of a degree
Experience with Python, PySpark, Git/Bitbucket, and cloud or distributed computing environments preferred
Experience supporting quantitative models within financial services preferred
Knowledge of CECL, CCAR, stress testing, model monitoring, model governance, or regulatory reporting processes preferred
Exposure to machine learning, AI, predictive modeling, or advanced analytics techniques preferred
Understanding of banking products, credit risk, and regulatory frameworks preferred
Experience in highly regulated environments preferred
Financial services experience preferred
No employment visa sponsorship or STEM OPT
Bachelor's degree listed under Education
No required certifications or licenses

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 plan
Stock purchase plan
Dependent care reimbursement account
Back-up child/elder care
Adoption, surrogacy, and doula reimbursement
Educational assistance, including select programs fully paid
Robust wellness program with financial incentives
Maternity and/or parental leave
Up to 11 paid holidays each year
9 occasional absence days each year
15 to 25 vacation days each year, depending on career level and years of service
Incentive eligible, with payment based on company, business, and/or individual performance