Quantitative Data Engineer for Risk & AI

Bank of America; Town of Charlotte (NY); On-site; USD 68,000 - 127,000; Full time

Benefits offered by this job

Benefits eligible

Job summary

Bank of America is seeking a skilled engineer to design, develop, and implement scalable data and analytics solutions for Global Risk Management. You will collaborate with modelers, risk managers, and technologists to map current state and design the future data and analytics landscape.

The role emphasizes building domain-specific expertise in bank processes, applying software engineering, AI, and data science to automate and improve risk workflows.

Qualifications

• Analytical thinking and quantitative analysis to solve business, risk, data, and technology challenges.
• Strong communication to explain complex concepts to diverse audiences.
• Experience with software engineering and AI development patterns and tools.

Responsibilities

• Applies quantitative methods to develop capabilities that meet line of business, risk management and regulatory requirements.
• Understands financial data: schemas, flow, size, data issues, data controls, etc.
• Builds performant big data pipelines
• Uses programming skills and SDLC knowledge to deliver high quality code for model and testing processes
• Collaborates with key stakeholders across the Bank to understand modeling and testing business processes and requirements
• Thinks outside the box to develop innovative approaches
• Maintains and enhances capabilities over time to respond to changing portfolios and risks

Skills

Analytical Thinking

Stakeholder Management

Software Engineering

Data Engineering

AI Development

Education

Bachelor’s degree required

Tools

Python

SQL

APIs

Job description

Bank of America is seeking a skilled engineer to design, develop, and implement scalable data and analytics solutions for Global Risk Management. You will collaborate with modelers, risk managers, and technologists to map current state and design the future data and analytics landscape.

The role emphasizes building domain-specific expertise in bank processes, applying software engineering, AI, and data science to automate and improve risk workflows.