Senior Quant Engineer, Risk Analytics & Data Pipelines

Bank of America; Jersey City (NJ); On-site; USD 120,000 - 180,000; Full time

Job summary

Bank of America in Jersey City is seeking a Senior Quantitative Engineer to design and oversee scalable software components that underpin GRM's data and analytics. You will work with senior modelers, risk managers, and technologists to map current state and architect the future data stack across big data pipelines and risk models.

This role focuses on applying quantitative methods to meet regulatory requirements, building reusable tools, and maintaining capabilities as portfolios and market

Qualifications

• Proven ability to design scalable software components for data-intensive systems.
• Experience applying quantitative methods to risk and regulatory needs.
• Strong programming and software development lifecycle knowledge.

Responsibilities

• Seek opportunities for consistent improvement in quality and efficiency.
• Collaborate with senior stakeholders across Global Risk Analytics and Enterprise Independent Testing, Front Line Units, Technology, Audit and Compliance.
• Provide leadership and oversight to less experienced team members.
• Applying quantitative methods to develop capabilities that meet line of business, risk management and regulatory requirements.
• Understanding financial data: schemas, flows, data issues, data controls, etc.
• Building performant big data pipelines.
• Use programming skills and knowledge of software development lifecycle principles to deliver high quality code for model and testing processes.
• Collaborate with key stakeholders across the Bank to understand modeling and testing business processes and requirements.

Skills

Software engineering

Big data

Modeling

Data analytics

Education

Bachelor's degree in Computer Science

Job description

Bank of America in Jersey City is seeking a Senior Quantitative Engineer to design and oversee scalable software components that underpin GRM's data and analytics. You will work with senior modelers, risk managers, and technologists to map current state and architect the future data stack across big data pipelines and risk models.

This role focuses on applying quantitative methods to meet regulatory requirements, building reusable tools, and maintaining capabilities as portfolios and market