Quantitative Data Engineer — Risk Analytics

Bank of America; Jersey City (NJ); On-site; USD 68,000 - 127,000; Full time

Benefits offered by this job

Benefits package

Paid time off

Job summary

Bank of America seeks a data engineering-focused professional to design, build, test, and implement scalable data tools for Global Risk Management. You will work with modelers, risk managers, and technologists to shape current and future data and analytics capabilities.

Responsibilities include building big data pipelines, applying quantitative methods, and ensuring governance, security, and auditability of AI-enabled solutions while aligning with regulatory requirements and business needs.

Qualifications

• Analytical Thinking & Problem Solving to solve business, risk, data, and technology challenges.
• Clear communication with stakeholders to align requirements and outcomes.
• Software engineering and AI development practices for scalable analytics solutions.
• Experience with structured and unstructured data, SQL, APIs, and databases.

Responsibilities

• Apply quantitative methods to meet risk management and regulatory requirements.
• Understand financial data schemas, flows, size, and data issues.
• Build performant big data pipelines.
• Deliver high quality code for model and testing processes.
• Collaborate with stakeholders across the Bank to interpret processes and requirements.
• Develop innovative approaches beyond current industry standards.
• Maintain and enhance capabilities as portfolios and risks evolve.
• Collaborate with process owners, risk managers, and technologists to assess current state processes.

Skills

Analytical Thinking

Problem Solving

Communication & Stakeholder Management

Software Engineering & AI Development

Data Engineering & Analytics

Education

Bachelor’s degree in related field or equivalent work experience

Job description

Bank of America seeks a data engineering-focused professional to design, build, test, and implement scalable data tools for Global Risk Management. You will work with modelers, risk managers, and technologists to shape current and future data and analytics capabilities.

Responsibilities include building big data pipelines, applying quantitative methods, and ensuring governance, security, and auditability of AI-enabled solutions while aligning with regulatory requirements and business needs.