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

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Expertise in developing and implementing wholesale credit risk models, including loss forecasting and behavioral scores, with strong analytical skills to conduct in-depth performance analysis. Proficient in programming languages such as R, Python, and SQL, and experienced in managing complex data architectures and machine learning solutions.

Highest-signal resume keywords

Credit Risk Model DevelopmentQuantitative AnalyticsData Architecture ManagementMachine Learning SolutionsStakeholder Communication

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Credit Risk ModelingLoss ForecastingBehavioral ScoringProgramming (R, Python, SAS, SQL)Data AnalysisData MiningMachine LearningStatistical AnalysisDatabase ManagementComplex Modeling

Soft Skills

Analytical SkillsProblem-Solving SkillsLeadership SkillsCommunication SkillsProject Management

Tools & Technologies

HadoopAlteryxTableauMicroStrategyLaTeX

Industry Keywords

Wholesale Credit RiskRegulatory Capital ModelsModel Risk ManagementData VisualizationData Science

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, review, and stakeholder interaction
Independently conduct quantitative analytics and complex modeling projects
Lead development of new models, analytical processes, and system approaches
Create documentation for all activities
Collaborate 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, 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 data-supported recommendations and conclusions
Ability to present findings and conclusions to senior leaders
Demonstrated leadership and influence skills
Ability to work in a large, complex organization and influence stakeholders
Strong communication skills with technical and non-technical audiences
Ability to work in a highly controlled and audited environment
Effective prioritization and time and project management
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 spanning teams

Benefits

Comp & perks

Annual discretionary incentive plan eligibility
Industry-leading benefits
Paid time off
Resources and support to employees
In-office culture with role-specific flexibility
Opportunities to learn, grow, and make an impact