Quantitative Finance Analyst

Bank of America

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

Posted 10/8/2026full-timeUnited StatesJuniorMid-Level💰 $89,800 - $155,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in quantitative analytics, model development, and statistical analysis, with strong programming skills in Python and SQL. Capable of translating complex quantitative findings into actionable business insights while ensuring compliance with model risk management and governance standards.

Highest-signal resume keywords

Quantitative AnalyticsModel DevelopmentStatistical AnalysisPython ProgrammingMachine Learning

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical Model EstimationData AnalysisMachine Learning ModelingModel DocumentationFeature EngineeringModel Explainability TechniquesQuantitative DocumentationData ExtractionPerformance EvaluationModel Governance

Soft Skills

Analytical SkillsProblem-Solving SkillsCommunication Skills

Tools & Technologies

SQLHDFSHiveSparkPySparkScikit-learnXGBoostLightGBMGitJIRA

Industry Keywords

Model Risk ManagementRegulatory ExpectationsConsumer Credit RiskCCARCECLCollateral Risk ManagementResidential Real EstateMortgage OriginationHousing MarketsEconomic Drivers

Tech Stack

Tools & technologies

HDFSJenkinsPySparkPythonScikit-LearnSparkSQL

About the role

Key responsibilities & impact

Conduct quantitative analytics and modeling projects for specific business units or risk types
Develop new models, analytic processes, and systems approaches
Create technical and quantitative documentation
Work with Technology staff to design systems for running developed models
Perform end-to-end market risk stress testing, including scenario design, implementation, results consolidation, reporting, and analysis
Support planning and prioritization of quantitative work aligned with the bank’s strategy
Identify continuous improvements through reviews of model development and validation decisions, technical documentation, and effective challenges
Support model development and model risk management for business requirements and enterprise risk appetite
Provide methodological, analytical, and technical guidance to challenge and influence development and validation projects
Work with model stakeholders and senior management on submission and validation outcomes
Perform statistical analysis on large datasets and interpret results using qualitative and quantitative approaches
Develop and maintain risk and capital models and model systems across Retail and GWIM product lines
Architect, implement, maintain, improve, and integrate quantitative solutions on strategic GRA platforms
Build quantitative solutions for risk and capital management
Improve infrastructure, code efficiency, quantitative capabilities, and use of computational resources
Support model execution with the Technology Team
Collaborate with Enterprise Model Risk Management on model validations and issue resolution
Act as a subject matter expert on quantitative modeling techniques
Oversee model performance, model risk, and model governance for critical model portfolios

Requirements

What you’ll need

Master’s degree in a related field or equivalent work experience
Minimum of 2 years of relevant experience in statistics, data science, machine learning, model development, and other quantitative analysis
Experience in data analysis, statistical model estimation, machine learning modeling, implementation, testing, performance evaluation, and model documentation
Strong programming skills in Python, SQL, and related quantitative or data science libraries
Experience with large and complex datasets, including data extraction, transformation, validation, feature engineering, and quality review using SQL-based tools
Experience with HDFS, Hive, Spark, PySpark, and distributed data processing environments
Hands-on experience with machine learning or AI model development using Python-based frameworks such as scikit-learn, XGBoost, LightGBM, Random Forest, or related ensemble methods
Experience with model explainability and transparency techniques, such as SHAP, feature importance, partial dependence, or interpretable models
Ability to translate quantitative findings into business implications for residential property valuation, collateral risk, mortgage or home equity decision support, and model governance
Quantitative documentation experience, including technical writing and familiarity with LaTeX or similar tools
Strong analytical and problem-solving skills and ability to work independently
Ability to present quantitative analysis, model results, and recommendations to technical and non-technical stakeholders
Ability to work in the United States of America
Desired: CI/CD and software engineering tools including Git, JIRA, Confluence, Pytest, Jenkins, SonarQube, and code review practices
Desired: knowledge of residential real estate, housing markets, appraisal processes, mortgage origination or servicing, home equity lending, collateral risk management, and related economic drivers
Desired: familiarity with model risk management, regulatory expectations, governance processes, CCAR, CECL, consumer credit risk, or regulated banking model development environments

Benefits

Comp & perks

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