Data Scientist I

Bank of America

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

Posted 9/18/2026full-timeAtlanta • North Carolina • United StatesJuniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data analysis, machine learning, and artificial intelligence, with a strong focus on risk management and compliance within financial services. Proficient in translating complex data insights into actionable business strategies while adhering to model governance frameworks.

Highest-signal resume keywords

Data AnalysisMachine LearningArtificial Intelligence GovernanceStatistical AnalysisTechnical Writing

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Applied StatisticsFeature EngineeringMachine Learning FrameworksData VisualizationQuantitative Modeling

Soft Skills

Verbal CommunicationWritten CommunicationStakeholder Collaboration

Tools & Technologies

Scikit-LearnPyTorchTensorFlowREST APIsGitHub Copilot

Industry Keywords

Financial ServicesRisk ManagementModel GovernanceComplianceOperational Processes

Tech Stack

Tools & technologies

MicroservicesPyTorchScikit-LearnTensorflow

About the role

Key responsibilities & impact

Analyze and interpret large datasets to identify revenue generation opportunities and develop risk management strategies
Collaborate with stakeholders to understand business problems and devise analytical solutions
Perform business analytics, including data analysis, trend identification, and pattern recognition, using machine learning, text mining, and statistical analysis
Apply agile practices for project management, solution development, deployment, and maintenance
Create and maintain technical documentation for business requirements, specifications, and production implementation
Manage quantitative models, data science products, data analysis reports, and data visualizations while maintaining quality and timeliness
Present technical concepts and analysis results to diverse internal stakeholders
Identify potential issues and develop controls to mitigate risk
Research advances in data science and artificial intelligence
Support AI and model development across the full product lifecycle, from ideation through retirement, across multiple lines of business
Work with senior model owners, developers, and users to streamline manual processes, improve decision-making, and deliver scalable, compliant solutions
Identify opportunities to reuse existing AI technologies, models, and methodologies and share best practices
Support Bank of America's Enterprise AI Catalyst program and AI enablement strategy

Requirements

What you’ll need

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field
1+ years of related work experience
Good, applied statistics skills, such as distributions, statistical testing, and feature engineering
Understanding and applied knowledge of artificial intelligence and machine learning modelling techniques
Excellent understanding of how Artificial Intelligence is used and governed in large regulated US financial institutions
Technical writing skills
Knowledge of AI and model governance frameworks within large, complex organizations
Experience interacting with, influencing, and communicating with senior business leaders
Strong verbal and written communication skills
Ability to translate complex analytical concepts and technical findings into clear, actionable business recommendations
Experience with machine learning frameworks such as scikit-learn, PyTorch, or TensorFlow
Experience building GenAI applications, copilots, agents, or workflow automation solutions
Familiarity with model governance, model risk management, or AI governance frameworks
Experience with REST APIs, microservices, and enterprise application integration
Experience with software testing, code reviews, and development best practices
Experience in financial services, risk management, compliance, audit, or operational processes
Experience using GitHub Copilot and VS Code

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 supporting collaboration, engagement, and career development
Appropriate flexibility based on role-specific responsibilities and business needs