Quantitative Engineer: Data Pipelines & AI Risk

Bank of America; Atlanta (GA); On-site; USD 90,000 - 156,000; Full time

Benefits offered by this job

Benefits eligible

Industry-leading benefits

Discretionary incentive program

Job summary

Bank of America is seeking a Software Engineer within Global Risk Analytics to design, develop, test, and implement scalable data tools for risk and capital management. You will work with modelers, risk managers, and technologists to shape data and analytics capabilities that support regulatory and business needs.

The role emphasizes SDLC-driven software engineering, big data pipelines, and collaboration across stakeholders to deliver robust, compliant solutions with AI-enabled approaches as

Qualifications

• Bachelor's degree or higher in fields like Mathematics, CS, Statistics, OR equivalent work experience.
• At least 2 years of software engineering experience in Quantitative Finance or related industry.

Responsibilities

• Apply quantitative methods to meet business, risk, and regulatory requirements.
• Understand financial data schemas, flow, and data issues.
• Build performant big data pipelines.
• Develop high-quality code for model and testing processes within SDLC.
• Collaborate with stakeholders across the Bank to understand and implement requirements.
• Innovate beyond current industry standards to improve solutions.
• Maintain and enhance capabilities to adapt to changing portfolios and risks.

Skills

Analytical thinking

Risk management

Communication

Software engineering

Python

Data modeling

Education

Bachelor's degree or above in Mathematics, CS, Statistics, OR related fields

Tools

Python

SDLC

APIs

SQL

LLM platforms

Job description

Bank of America is seeking a Software Engineer within Global Risk Analytics to design, develop, test, and implement scalable data tools for risk and capital management. You will work with modelers, risk managers, and technologists to shape data and analytics capabilities that support regulatory and business needs.

The role emphasizes SDLC-driven software engineering, big data pipelines, and collaboration across stakeholders to deliver robust, compliant solutions with AI-enabled approaches as