Quantitative Engineer Analyst

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.

We commit to an inclusive workplace, attracting and developing exceptional talent, supporting our teammates’ physical, emotional, and financial wellness, recognizing and rewarding performance, and making an impact in the communities we serve.

Global Risk Analytics (GRA) and Enterprise Independent Testing (EIT) are sub-lines of business within Global Risk Management (GRM). Collectively, they are responsible for developing a consistent and coherent set of models, analytical tools, and tests for effective risk and capital measurement, management and reporting across Bank of America. GRA and EIT partner with the Lines of Business and Enterprise functions to ensure the capabilities it builds address both internal and regulatory requirements, and are responsive to the changing nature of portfolios, economic conditions and emerging risks.

In executing its activities, GRA and EIT drive innovation, process improvement and automation.

Quantitative Engineer Analyst is the entry level role to becoming a Quantitative Engineer. Quantitative engineers in Global Risk are responsible for designing and implementing common, reusable, and scalable software components. These components enable GRM’s data and analytical capabilities. They can be domain independent—e.g., generic data quality tools over trillions of rows of data—or domain specific—e.g., classification models for surveillance or testing framework for Global Markets processes.

Quantitative engineers work with modelers, risk managers, and technologists to understand the current state and design the future state of data and analytics. They combine software engineering, big data, and modeling skills and work across the entire spectrum of a big data stack—from data to logic to model to UI to UX.

• Understanding financial data: schemas, flow, size, data issues, data controls, etc.
• Building performant big data pipelines.
• Using programming skills and knowledge of software development lifecycle principles to deliver high quality code for model and testing processes.
• Collaborating with key stakeholders across the Bank to understand modeling and testing business processes and requirements.
• Thinking outside the box of current industry standards to develop innovative approaches.
• Maintaining and continuously enhancing capabilities over time to respond to the changing nature of portfolios, economic conditions, and emerging risks.
• Source and evaluate data required for modeling and testing.
• Design, develop and implement models and tests.
• Produce clear, concise and repeatable technical documentation on models and tests for internal and regulatory purposes.

• High level of intellectual curiosity.
• Feel ownership and accountability for delivering high quality work, prioritizing effectively, adapting, and meeting strict deadlines.
• Strong written, verbal, presentation creation and delivery skills.
• Well organized, with attention to detail.
• Ability to adjust to new conditions and changes effectively.
• Capacity to notice and consider all aspects of a task or project.
• Work effectively with others toward a common goal.

• Bachelor’s degree in Computer Science, a closely related field, or a degree from a program where software engineering was a key focus.

• Strong programming skills (e.g., Python).
• Strong analytical and problem‑solving skills.
• Digital fluency.

• Shift: 1st shift (United States of America).
• Hours Per Week: 40.
• Seniority level:
  Entry level.
• Employment type:
  
  Full‑time.
• Job function:
  Research, Analyst, and Information Technology.
• Industries:
  Banking.