Data Scientist I

Support AI and model development across the full product lifecycle while contributing to risk analytics, governance, and analytics modernization.

Responsibilities

• Perform business analytics including data analysis, trend identification, and pattern recognition using techniques such as machine learning, text mining, and statistical analysis to drive data-driven insights
• Apply agile practices for project management, solution development, deployment, and maintenance
• Create and maintain technical documentation that captures business requirements and specifications for analytical solutions and their implementation in production
• Manage multiple priorities while delivering high-quality, timely outputs such as quantitative models, data science products, data analysis reports, and data visualizations; work effectively independently and in a team setting
• Deliver presentations and participate in in-person and virtual discussions to communicate technical concepts and analysis results to internal stakeholders
• Mitigate risk by identifying potential issues and developing controls
• Research recent advances in data science and artificial intelligence to support business analytics
• Contribute to AI and model development activities supporting business challenges from ideation through retirement across multiple LOBs
• Streamline manual processes, improve decision-making, and deliver measurable ROI through scalable, compliant, integrated solutions
• Share cross-functional insights to identify opportunities to leverage existing AI technologies, models, and methodologies to avoid duplication and promote reuse
• Support the Bank of America Enterprise AI Catalyst program and contribute to the company AI enablement strategy

Requirements

• Demonstrated ability to foster an innovative culture while interacting with, influencing, and communicating with senior business leaders
• Strong track record of challenging the status quo, identifying improvement opportunities, and driving organizational change
• Knowledge of AI and model governance frameworks within large, complex organizations
• Strong interpersonal skills with the ability to build credibility and collaborate across all levels of the organization
• Excellent verbal and written communication skills, including the ability to build trusted relationships and influence diverse stakeholders
• Ability to translate complex analytical concepts and technical findings into clear, actionable recommendations for both technical and non-technical audiences
• Education: Bachelor’s or Master’s degree in a related quantitative field (Data Science, Computer Science, Statistics, Mathematics, Engineering, or similar)
• Experience: 1+ years of related work experience
• Good, applied statistics skills including distributions, statistical testing, and feature engineering
• Understanding and applied knowledge of Artificial Intelligence and machine learning modeling techniques
• Excellent understanding of how AI is used and governed in a large regulated US financial institution
• Technical writing skills
• Additional context aligned to the role’s governance environment: support AI risk assessment and readiness activities where DSTRO serves as AI-DE

Technologies

• Machine learning
• Text mining
• Statistical analysis
• Artificial Intelligence (AI)
• Agile practices
• Artificial Intelligence and machine learning modeling techniques

Additional Team Context

• Global Risk Analytics (GRA) is responsible for consistent, coherent models and analytical tools for risk and capital measurement, management, and reporting
• GRA supports model implementation, execution, forecasting, and performance monitoring, driving innovation, process improvement, and automation
• Data Science for Technology, Risk and Operations (DSTRO) enables responsible AI adoption via governance, model oversight, model development, and enterprise data engineering
• AI-DE reviews and challenges AI Risk Assessments and AI Readiness Tollgates for AI use cases where DSTRO serves as AI-DE
• Leverages AI subject matter expertise to assess supporting documentation for completeness, accuracy, sufficiency, and alignment to governance requirements (including Quantitative Methods Classification)

Skills

• Adaptability
• Attention to Detail
• Business Analytics
• Technical Documentation
• Written Communications
• Agile Practices
• Application Development
• Collaboration
• Data Visualization
• DevOps Practices
• Artificial Intelligence/Machine Learning
• Networking
• Policies, Procedures, and Guidelines Management
• Presentation Skills
• Risk Management

Location and Work Details

• Location: Atlanta, GA (onsite)
• Shift: 1st shift (United States of America)
• Hours per week: 40