Quantitative Engineer: Build Big-Data Risk Models

Bank of America; Jersey City (NJ); On-site; USD 90,000 - 156,000; Full time

Benefits offered by this job

Industry-leading benefits

Discretionary incentive

Job summary

Bank of America in Jersey City is seeking a quantitative engineer to design, develop, test and implement reusable software components for data quality tools and surveillance frameworks within Global Risk Analytics.

You will work with modelers, risk managers and technologists to shape the data and analytics roadmap, build big data pipelines, and contribute to regulatory-compliant modeling efforts.

Qualifications

• Bachelor’s degree in related field or equivalent work experience.
• 1-2 years of relevant professional experience or demonstrable coding projects.
• Strong Python development skills and SDLC knowledge.
• Experience with big data technologies and distributed computing.

Responsibilities

• Apply quantitative methods to develop capabilities meeting risk and regulatory requirements.
• Understand financial data schemas, flows, and data quality issues.
• Build and optimize big data pipelines for model and testing processes.
• Deliver high-quality code across data modeling and testing workflows.
• Collaborate with stakeholders to align modeling and testing needs.

Skills

Python

Spark

Hadoop

Pandas

React

JavaScript

Automation

Data Analytics

Education

Bachelor’s degree in related field

Tools

Hive

PySpark

SQL

Job description

Bank of America in Jersey City is seeking a quantitative engineer to design, develop, test and implement reusable software components for data quality tools and surveillance frameworks within Global Risk Analytics.

You will work with modelers, risk managers and technologists to shape the data and analytics roadmap, build big data pipelines, and contribute to regulatory-compliant modeling efforts.