Quantitative Finance Analyst

Bank of America

. Conduct end-to-end market risk stress testing, including scenario design, implementation, results consolidation, reporting, and analysis .

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

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Expertise in developing and validating credit risk models, including loss forecasting and regulatory capital models, while leveraging strong programming skills in R, Python, and SQL. Proven ability to conduct statistical analysis on large datasets and communicate findings effectively to senior management.

Highest-signal resume keywords

Credit Risk Model DevelopmentStatistical AnalysisProgramming Skills (R, Python, SQL)Data Analytics and VisualizationProject Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Credit Risk ModelsStatistical AnalysisData MiningMachine LearningData ArchitectureModel ValidationQuantitative AnalysisDatabase ManagementScenario DesignLoss Forecasting

Soft Skills

Analytical SkillsProblem-SolvingCommunication SkillsLeadershipStrategic Thinking

Tools & Technologies

HadoopAlteryxTableauMicroStrategyLaTeX

Industry Keywords

Market RiskModel Risk ManagementData ScienceFinancial Data AnalysisEnterprise Risk Appetite

Tech Stack

Tools & technologies

HadoopPythonSQLTableau

About the role

Key responsibilities & impact

Conduct end-to-end market risk stress testing, including scenario design, implementation, results consolidation, reporting, and analysis
Plan quantitative work priorities in line with the bank’s overall strategy
Identify continuous improvements through model development and validation reviews
Support model development and model risk management for business requirements and enterprise risk appetite
Provide methodological, analytical, and technical guidance for development and validation projects
Work with model stakeholders and senior management regarding submission and validation outcomes
Perform statistical analysis on large datasets using qualitative and quantitative approaches
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 monitoring and stakeholder interactions
Develop models, analytic processes, and system approaches
Create technical documentation and collaborate with Technology staff on model 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, 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 narratives and recommendations
Ability to present findings and conclusions to senior leaders
Demonstrated leadership and broad peer influence
Ability to work in a large, complex organization and influence stakeholders
Ability to work independently and collaboratively
Strong communication skills with technical and non-technical audiences
Ability to work in a highly controlled and audited environment
Prioritization, time and project management skills
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 datasets
Experience with data mining and advanced analytical techniques
Experience managing large datasets using 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
Experience managing project tasks and timelines across teams
Experience engineering complex, multifaceted cross-team processes and improving workflows

Benefits

Comp & perks

Affordable, competitive and flexible benefits
Support for physical, emotional, and financial wellness
Opportunities to learn, grow, and make an impact
In-office culture with role-specific flexibility
Career development opportunities