Quantitative Engineer Analyst

Bank of America; Charlotte (NC); On-site; USD 120,000 - 160,000; Full time

Job summary

Bank of America in Charlotte, NC is seeking a Global Risk Analytics professional to design and implement technical solutions that enhance data, testing, and analytics within GRM. You will collaborate with risk managers, data owners, and technologists to assess processes and improve controls.

Leveraging software engineering, big data, data science, and risk management skills, you will build scalable data pipelines and automated workflows while ensuring governance and security for AI-enabled

Qualifications

• Bachelor’s degree or higher in Mathematics, Computer Science, Statistics, Operations Research, Data Science or related field.
• Experience in software engineering, data analytics, and risk management domains.
• Ability to work with large data sets to solve analytical problems.
• Proficiency in Python and SQL.

Responsibilities

• Understand bank processes, data flows, and controls to inform technical designs.
• Collaborate with process owners, risk managers, and technologists to assess current state.
• Design scalable data pipelines and analytical solutions for risk management.
• Apply quantitative techniques to identify trends and assess risk.
• Ensure AI-enabled solutions meet governance, security, and auditing requirements.

Skills

Analytical Thinking

Communication

Software Engineering & AI Development

Data Engineering & Analytics

Education

Bachelor’s degree or higher

Job description

Job Description

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 and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates’ physical, emotional, and financial wellness through affordable, competitive and flexible benefits.

We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve.

Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs.

At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!

About Us Summary

Global Risk Analytics (GRA) is a sub-line of business within Global Risk Management (GRM). The GRA team provides quantitative capabilities supporting global risk management and capital management and develops a consistent set of risk and capital models, tests and analytical tools that support decision making across the bank.

Job Profile Summary

This job is responsible for obtaining an understanding of bank processes - including underlying data, flows, and controls – and designing and implementing technical solutions to enhance Global Risk Management’s (GRM) data, testing, and analytical capabilities. Key responsibilities include collaborating with process owners, risk managers, and technologists to assess current state processes, underlying data, process flows and risks. Job expectations include building domain-specific expertise in bank processes and data, and applying a combination of software engineering, big data, data science and risk management skills to drive the technical solution implementation and automate processes.

Responsibilities

• Analytical Thinking & Risk Management: Apply critical thinking, sound judgment, risk management principles to understand business processes, controls, and risks to influence appropriate designs for technical solutions to business problems.
• Stakeholder Engagement & Communication: Partner with process owners, data owners, Front Line Units, Technology teams, and other stakeholders to understand business requirements and build understanding of the firms processes and technology landscape.
• Solution Development & Engineering: Leverage programming expertise, software development lifecycle (SDLC) principles, and AI development patterns to build and document scalable analytical solutions that support business objectives, regulatory requirements, and operational efficiency.
• Data Engineering & Analytics: Source, validate, and analyze data while designing scalable data pipelines and analytical solutions across large and complex datasets. Apply quantitative and analytical techniques to identify trends, assess risk.
• AI Governance & Operational Excellence: Understand governance, security, observability, and auditability control requirements for AI-enabled solutions including continuous monitoring of performance. Develop understanding on how to drive process optimization, and enhance solution effectiveness through testing, feedback loops, automation, and responsible AI adoption.

Minimum Education Requirements

• Bachelor’s degrees or above in fields including but not limited to: Mathematics, Computer Science, Statistics, Process and Mechanical Engineering, Operations Research, Data Science (or equivalent work experience)

Required Skills

• Analytical Thinking & Problem Solving: Applies structured thinking, quantitative analysis, and sound judgment to solve business, risk, data, and technology challenges.
• Communication & Stakeholder Management: Effectively communicates complex technical concepts to different audiences and able to build strong partnerships across stakeholders.
• Software Engineering & AI Development: Demonstrated strong programming skills (e.g., Python), analytical and problem-solving, digital fluency, and exposure to AI technologies, including large language models (LLMs), agentic AI concepts, or AI-assisted development tools through coursework, internships, personal projects, or professional experience.
• Data Engineering & Analytics: Experience working with structured and unstructured data, SQL, APIs, and databases to source, analyze, and integrate data while solving analytical problems.

Skills

• Analytical Thinking
• Critical Thinking
• Oral Communications
• Prioritization
• Written Communications
• Attention to Detail
• Change Management
• Collaboration
• Presentation Skills

Shift

1st shift (United States of America)

Hours Per Week

40