Quantitative Data Engineer

HITEC; Chicago (IL); Hybrid; USD 90,000 - 156,000; Full time

Benefits offered by this job

Benefits eligible

Discretionary bonus

Job summary

Bank of America in Chicago, IL seeks a data-focused Software Engineer for Global Risk Analytics. You will design, develop, test, and implement scalable data quality tools and models supporting risk management and regulatory needs.

You will collaborate with modelers, risk managers and technologists to shape the future state of data and analytics in a fast-paced environment. Strong Python, SDLC, and big data tool experience are essential.

Qualifications

• Bachelor's degree in Computer Science or equivalent
• 1-2 years of relevant experience or strong coding projects
• Strong Python and SDLC knowledge
• Experience with quantitative methods and data analytics
• Experience with large-scale data sets and big data tools
• Experience building data-driven applications using React/JavaScript

Responsibilities

• Apply quantitative methods to develop capabilities meeting risk and regulatory requirements
• Understand and model financial data schemas, flows, and controls
• Build performant big data pipelines
• Deliver high-quality code for models and testing processes
• Collaborate with stakeholders to align modeling and testing requirements
• Think innovatively to improve existing analytics approaches
• Maintain and evolve data capabilities over time to address changing portfolios and risks
• Source and evaluate data for modeling and testing
• Design, develop, and implement models and tests
• Produce clear technical documentation for models and tests

Skills

Python

Big data

Data modeling

Spark

SQL

ML basics

Education

Bachelor's degree in Computer Science

Tools

Pandas

Hadoop

Hive

React

Job description

Bank of America in Chicago, IL seeks a data-focused Software Engineer for Global Risk Analytics. You will design, develop, test, and implement scalable data quality tools and models supporting risk management and regulatory needs.

You will collaborate with modelers, risk managers and technologists to shape the future state of data and analytics in a fast-paced environment. Strong Python, SDLC, and big data tool experience are essential.