At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.
Being a Great Place to Work is core to how we drive Responsible Growth. This includes our commitment to being an inclusive workplace, attracting and developing exceptional talent, supporting our teammates' physical, emotional, and financial wellness, recognizing and rewarding performance, and how we make an impact in the communities we serve.
Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations.
At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!
Job Description:
This job is responsible for creating technical plans from requirements expressed in a non-technical language and delivering components of the project. Key responsibilities include ability to effectively structure and communicate information to senior leaders and write logically developed documents for clear documentation. Job expectations include understanding the work stream's purpose and key business aspects and understanding the model development cycle.
This role focuses on incorporating analytical knowledge into digestible context and leveraging the bank's internal data sources and GenAI models to develop tools that enable stakeholders to access insights quickly. Job expectations include working knowledge of financial products across Consumer, Business, and Wealth Management and the ability to work both independently and collaboratively with team members.
Responsibilities:
Demonstrates an advanced understanding of statistical modeling requirements expressed in a technical language and executes per a specified plan and timeline
Builds basic multivariate statistical models and makes logical inferences of relevant statistical assumptions
Analyzes and sanitizes large volumes of data
Communicates and collaborates with direct manager, peers and business partners
Produces structured and organized documentation; writes code that is well documented and easy to understand
Leverage GenAI based tools that take natural-language queries and return insights from large datasets
Develop and implement LLM-based solutions to enhance data analysis and insight generation.
Research and evaluate new models and methods (prompting, fine-tuning, embeddings, evaluation harnesses, and guardrails), and develop lightweight prototypes that can be productionized
Skills:
Data Mining
Model Development
Artificial Intelligence/Machine Learning
Oral Communications
Problem Solving
Risk Modeling
Technical Documentation
Analytical Thinking
Business Acumen
Innovative Thinking
Presentation Skills
Written Communications
Generative AI Models
Strong hands-on programming experience in Python and SQL.
Knowledge of Unix based environment and shell programming
Excellent analytical and problem-solving skills.
Required Qualifications:
Strong Python development skills with production-quality engineering practices.
Data and infrastructure experience: SQL, Starburst, Teradata, Hadoop, Linux/Unix, and cloud-native or distributed systems.
Experience with LLMs and agent frameworks: LangGraph, LangChain, OpenAI-compatible APIs, MCP, vLLM/Triton, multi-agent orchestration, and advanced prompt engineering.
Desired Qualifications:
3+ years of directly relevant experience
Advanced degree in engineering, computer science, statistics or another heavy quantitative discipline
Software engineering experience: FastAPI services, containerization, model deployment, and monitoring.
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