Data Scientist I – Model Governance, Fraud Prevention and Detection

Bank of America

. Analyze and interpret large datasets to identify revenue opportunities and develop risk management strategies .

Posted 10/15/2026full-timeUnited StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data analysis, model validation, and risk management within financial services, utilizing advanced analytical skills and proficiency in SQL, SAS, and Python. Capable of producing technical documentation and collaborating effectively with stakeholders to drive data-driven solutions.

Highest-signal resume keywords

Model ValidationData AnalysisSQL ProficiencySAS ProficiencyTechnical Writing

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data AnalysisModel ValidationStatistical AnalysisMachine LearningText MiningTrend IdentificationPattern RecognitionQuantitative AnalysisRisk ManagementModel Monitoring

Soft Skills

Analytical SkillsProblem-SolvingCommunication SkillsCollaborationIntellectual Curiosity

Tools & Technologies

SQLSASPythonAgile PracticesData Visualization

Certifications & Qualifications

Quantitative DegreeRelevant Certifications

Industry Keywords

Financial ServicesModel GovernanceSR-26-2 GuidanceComplianceTechnical Documentation

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Analyze and interpret large datasets to identify revenue opportunities and develop risk management strategies
Collaborate with stakeholders to understand business problems and devise data-driven solutions
Perform business analytics, data analysis, trend identification, and pattern recognition using machine learning, text mining, and statistical analysis
Apply agile practices to project management, solution development, deployment, and maintenance
Create and maintain technical documentation for business requirements, specifications, and production implementation
Manage multiple priorities and deliver quantitative models, data science products, analysis reports, and data visualizations
Present technical concepts and analysis results to internal stakeholders and foster collaboration
Identify potential issues, develop controls, and mitigate risk
Research advances in data science and artificial intelligence
Develop technical documentation for internally and vendor-developed models
Work with developers to understand model operation, challenge methodology, and verify result accuracy
Partner with technology and model users to schedule deployments and plan future model installations
Work with model risk management, legal, and compliance teams to validate and approve models
Produce analytics to verify early model results
Conduct regular model monitoring and share performance results and insights
Support Bank policy and governance requirements for artificial intelligence models
Track post-deployment model changes and maintain documentation
Drive granular model performance monitoring, trend detection, root cause analysis, and gap analysis

Requirements

What you’ll need

Quantitative degrees (either undergraduate or graduate) or relevant certifications and experience
Minimum of 3 years of experience in model validation or development
Experience with model governance, model documentation, model monitoring, and interactions with model risk management functions
Strong analytical skills, including investigating performance trends, identifying root causes, and recommending solutions
Proficiency with SQL and SAS
Excellent technical writing skills
Critical problem-solving abilities, including data selection and solution deployment
Excellent communication and influencing skills
Ability to thrive in a fast-paced and highly dynamic environment
Intellectual curiosity and ability to investigate problems and develop creative solutions
Advanced quantitative degree (Master’s or PhD) preferred
5+ years of experience working in model validation preferred
Experience in financial services and following SR-26-2 guidance desirable
Working knowledge of Python highly desired
40 hours per week
1st shift (United States of America)

Benefits

Comp & perks

Affordable, competitive and flexible benefits
Support for teammates’ physical, emotional, and financial wellness
Opportunities to learn, grow, and make an impact
Inclusive workplace and career development opportunities
In-office culture supporting collaboration, engagement, and career development