Job Description:
This job is responsible for analyzing and interpreting large datasets to uncover potential revenue generation opportunities and develop effective risk management strategies. Key responsibilities include collaborating with key stakeholders to comprehend business problems, utilizing data gathering and analysis techniques to devise solutions, and presenting recommendations based on the findings. Job expectations include demonstrating flexibility, resilience, accountability, a disciplined approach, and a commitment to fostering responsible growth for the enterprise.

Responsibilities:

• Performs business analytics, which includes data analysis, trend identification, and pattern recognition, using advanced techniques (e.g., machine learning, text mining, statistical analysis, etc.) to support decision-making and drive data-driven insights

• Applies agile practices for project management, solution development, deployment, and maintenance

• Creates and maintains technical documentation, capturing the business requirements and specifications related to the developed analytical solution and its implementation in production

• Manages multiple priorities and maintains quality and timeliness of work deliverables such as quantitative models, data science products, data analysis reports, or data visualizations, while exhibiting the ability to work independently and in a team environment

• Delivers engaging presentations and engages in both in-person and virtual conversations that effectively communicate technical concepts and analysis results to a diverse set of internal stakeholders, and develops professional relationships to foster collaboration on work deliverables

• Mitigates risk by identifying potential issues and developing controls

• Researches the latest advances in the fields of data science and artificial intelligence to support business analytics

Global Risk Analytics (GRA) is a sub-line of business within Global Risk Management (GRM), responsible for developing a consistent and coherent set of models and analytical tools for effective risk and capital measurement, management and reporting across the bank. GRA is also responsible for model implementation, execution, forecasting and performance monitoring. The team drives innovation, process improvement and automation across these activities. 

Overview of  Data Science for Technology, Risk and Operations:
Data Science for Technology, Risk, and Operations (DSTRO) enables the Bank's responsible adoption of Artificial Intelligence (AI) through governance, model oversight, model development, and enterprise data engineering. By providing AI and model risk governance, AI-driven solutions, and critical transaction data assets, DSTRO delivers the controls, infrastructure, and insights needed to strengthen risk management, enhance operational effectiveness, and drive enterprise value.​

Team Overview: 
Artificial Intelligence Development Executive (AI-DE) team reviews, challenges, and approves AI Risk Assessments and AI Readiness Tollgates for all AI use cases where DSTRO serves as AI-DE. Leverages technical AI subject matter expertise to assess supporting documentation including Quantitative Methods Classification for completeness, accuracy, sufficiency, and adherence to governance requirements.​ 

Role Description:
As a Data Scientist I, you will support AI and model development activities that address key business challenges throughout the full product lifecycle, from ideation through retirement, across multiple lines of business (LOBs) at Bank of America.

You will work directly with senior model owners, developers, and users across these LOBs. In supporting model development, you will focus on streamlining manual processes, improving decision-making, and delivering measurable ROI through scalable, compliant, and integrated solutions. You will also provide cross-functional insights and identify opportunities to leverage existing AI technologies, models, and methodologies across the bank to avoid duplication, promote reuse, and share best practices.

This role provides a unique opportunity to directly support Bank of America's Enterprise AI Catalyst program and contribute to the company's AI enablement strategy. The successful candidate will possess a balanced combination of relationship management, project management, and strong, proven data science expertise.

Required Skills:

• Demonstrated ability to foster an innovative culture while effectively interacting with, influencing, and communicating with senior business leaders.

• Strong track record of challenging the status quo, identifying opportunities for improvement, and driving organizational change.

• Knowledge of AI and model governance frameworks within large, complex organizations.

• Excellent interpersonal skills with the ability to build credibility and collaborate effectively across all levels of the organization.

• Strong verbal and written communication skills, with a demonstrated ability to build trusted relationships and influence diverse stakeholders.

• Ability to translate complex analytical concepts and technical findings into clear, actionable business recommendations for technical and non-technical audiences.

Required Technical Skills:

• 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, feature engineering

• Understanding and applied knowledge of Artificial Intelligence and machine learning modelling techniques

• Excellent understanding of how Artificial Intelligence is used and governed a large regulated US financial institutions

• Technical writing skills

Desired Skills:

• 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 working 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 modern AI development tools such as GitHub Copilot and VS Code

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

Hours Per Week:

Travel Required: