Quantitative Finance Analyst

Bank of America

. Conduct quantitative analytics and modeling projects for specific business units or risk types .

Posted 9/17/2026full-timeAtlanta • New Jersey • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and validating credit risk models, performing quantitative analytics, and conducting market risk stress testing. Proficient in statistical analysis, data management, and effective communication of complex findings to stakeholders.

Highest-signal resume keywords

Credit Risk Model DevelopmentStatistical AnalysisProgramming Skills (R, Python, SAS, SQL)Data Analytics and Visualization Tools (Alteryx, Tableau, MicroStrategy)Project Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Quantitative AnalyticsMarket Risk Stress TestingModel Development and ValidationData Mining TechniquesMachine Learning SolutionsComplex Data ArchitectureStatistical ModelingData Set ManagementScenario DesignLoss Forecasting

Soft Skills

Analytical Problem-SolvingCommunication SkillsLeadership SkillsStrategic ThinkingTeam Collaboration

Tools & Technologies

HadoopData Science Tools and LibrariesData WarehousesLaTeXTechnical Documentation

Industry Keywords

Financial Data AnalysisModel Risk ManagementRegulatory Capital ModelsData-Driven StorytellingComplex Organization Navigation

Tech Stack

Tools & technologies

HadoopPythonSQLTableau

About the role

Key responsibilities & impact

Conduct quantitative analytics and modeling projects for specific business units or risk types
Perform end-to-end market risk stress testing, including scenario design, implementation, results consolidation, reporting, and analysis
Support planning of quantitative work priorities aligned with the bank’s strategy
Identify continuous improvements through model development and validation reviews
Support model development and model risk management within focus areas
Provide methodological, analytical, and technical guidance for development and validation projects
Challenge and influence strategic and tactical approaches and identify potential risks
Communicate submission and validation outcomes to model stakeholders and senior management
Perform statistical analysis on large datasets and interpret qualitative and quantitative results
Develop wholesale credit risk models, including loss forecasting, commercial scorecards, behavioral scores, and regulatory capital models
Analyze wholesale credit performance and financial data
Prepare white papers for developed models
Interact with internal model risk management, address concerns, and remediate model-related findings
Support post-implementation activities, ongoing monitoring reviews, and stakeholder interactions
Develop new models, analytic processes, or system approaches
Create technical documentation for modeling activities
Work with Technology staff to design systems for running developed models
Extract, analyze, and merge data from disparate systems
Identify, assign, and manage project tasks and timelines across teams
Document process steps, inputs, outputs, and requirements; identify gaps and improve workflows

Requirements

What you’ll need

Master’s degree in Math, Economics, Statistics, Engineering, Finance, Computer Science or similar discipline
Minimum education requirement: Master’s degree in related field or equivalent work experience
5+ years professional experience developing credit risk models
Strong programming skills, e.g. R, Python, SAS, SQL or other languages
Strong analytical and problem-solving skills
Experience using and developing cross-sectional models
Experience implementing models into various production environments
Ability to create compelling data-driven stories and articulate conclusions
Ability to present findings, data, and conclusions to influence senior leaders
Demonstrated leadership skills and ability to influence peers
Ability to work in a large, complex organization and influence stakeholders and partners
Self-starter able to initiate work independently
Strong team player able to work individually and collaboratively
Strong communication skills for technical and non-technical audiences
Ability to work in a highly controlled and audited environment
Effective prioritization, time management, and project management
Strategic thinking and ability to understand complex business challenges
Experience with complex data architecture, data science tools and libraries, data warehouses, and machine learning
Ability to extract, analyze, and merge data from disparate systems
Experience developing and maintaining complex databases and data sets
Experience using data mining and advanced analytical techniques
Experience managing large data sets with tools such as Hadoop
Experience designing, developing, and applying scalable Machine Learning and Artificial Intelligence solutions
Experience with data analytics and visualization tools such as Alteryx, Tableau, and MicroStrategy
Experience with LaTeX
Experience building data architecture optimized for large dataset retrieval, analysis, storage, cleansing, and transformation
Ability to drive action and sustain momentum to achieve results
Ability to manage project tasks and timelines across teams
Experience engineering complex, multifaceted processes across teams and improving workflows

Benefits

Comp & perks

Affordable, competitive and flexible benefits
Support for teammates’ physical, emotional, and financial wellness
Opportunities to learn, grow, and make an impact
In-office culture supporting collaboration, engagement, and career development
Full-time employment
40 hours per week
1st shift