Quantitative Finance Analyst

Bank of America

. Develop wholesale credit risk models, including loss forecasting, commercial scorecards, behavioral scores, and regulatory capital models .

Posted 10/9/2026full-timeUnited StatesMid-LevelSenior💰 $89,800 - $155,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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

Expertise in developing and implementing wholesale credit risk models, including loss forecasting and behavioral scores, with strong analytical skills to conduct in-depth financial data analysis. Proficient in communicating complex model results to diverse stakeholders and managing projects in a highly controlled environment.

Highest-signal resume keywords

Credit Risk Model DevelopmentProgramming Skills in R, Python, SAS, SQLData Analytics and Visualization ToolsMachine Learning and Artificial Intelligence SolutionsLeadership and Stakeholder Influence

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Credit Risk ModelingQuantitative AnalyticsData Mining TechniquesComplex Data ArchitectureStatistical AnalysisBenchmarking and Sensitivity AnalysisDatabase ManagementModel ImplementationData Extraction and AnalysisProject Management

Soft Skills

Analytical Problem-SolvingCommunication SkillsTime ManagementPrioritizationInfluencing Peers

Tools & Technologies

HadoopAlteryxTableauMicroStrategyLaTeX

Industry Keywords

Wholesale Credit RiskRegulatory Capital ModelsModel Risk ManagementData Science ToolsProduction Environments

Tech Stack

Tools & technologies

HadoopPythonSQLTableau

About the role

Key responsibilities & impact

Develop wholesale credit risk models, including loss forecasting, commercial scorecards, behavioral scores, and regulatory capital models
Conduct in-depth analysis of 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 interaction
Independently conduct quantitative analytics and complex modeling projects
Lead development of new models, analytic processes, and system approaches
Document all activities and work with technology staff on systems to run developed models
Analyze bank model results using benchmarking and sensitivity analysis
Articulate model performance, accuracy, and remediation areas
Communicate model results to risk management, model development, model risk, senior management, and regulators

Requirements

What you’ll need

Master’s degree in Math, Economics, Statistics, Engineering, Finance, Computer Science or similar discipline
5+ years professional experience developing credit risk models
Strong programming skills in 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 data-supported recommendations and conclusions
Ability to present findings, data, and conclusions to senior leaders
Demonstrated leadership skills and ability to influence peers
Ability to work in a large, complex organization and influence stakeholders and partners
Strong communication skills for technical and non-technical audiences
Ability to work in a highly controlled and audited environment
Prioritization, time and project management skills
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 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
Experience managing project tasks and timelines across teams
Experience engineering complex, multifaceted processes across teams
Minimum education requirement: Master’s degree in related field or equivalent work experience

Benefits

Comp & perks

Affordable, competitive and flexible benefits
Support for physical, emotional, and financial wellness
Opportunities to learn, grow, and build a career
Annual discretionary incentive award eligibility based on individual, line of business/group, and company performance
Industry-leading benefits
Paid time off
Resources and support to make an impact and contribute to sustainable business and community growth