Quantitative Engineer – AI & Data Analytics

Bank of America; Atlanta (GA); On-site; USD 120,000 - 180,000; Full time

Job summary

Bank of America is seeking a data analytics professional to design and implement technical solutions that enhance Global Risk Management data, testing, and analytics capabilities. You will collaborate with process owners, risk managers, and technologists to assess current state processes and data flows, applying software engineering and AI development patterns.

Responsibilities include building scalable data pipelines, applying quantitative techniques, and ensuring governance and observability

Qualifications

• Analytical thinking, problem solving to understand business, risk, data and tech challenges.
• Strong communication with stakeholders across teams.
• Proficiency in Python and data engineering concepts for scalable analytics.
• Experience with structured and unstructured data, SQL and APIs to source and analyze data.
• Ability to design and implement scalable analytical solutions and AI-enabled patterns.

Responsibilities

• Apply critical thinking and risk management principles to influence technical designs.
• Partner with owners, data stewards, and technology teams to understand requirements.
• Build and document scalable analytical solutions supporting regulatory and business objectives.
• Source, validate, and analyze data while designing robust data pipelines.
• Ensure governance, security, and observability in AI-enabled solutions.

Skills

Analytical Thinking

Critical Thinking

Oral Communications

Prioritization

Written Communications

Attention to Detail

Change Management

Collaboration

Presentation Skills

Education

Bachelor’s degree

Tools

Python

SQL

Job description

Bank of America is seeking a data analytics professional to design and implement technical solutions that enhance Global Risk Management data, testing, and analytics capabilities. You will collaborate with process owners, risk managers, and technologists to assess current state processes and data flows, applying software engineering and AI development patterns.

Responsibilities include building scalable data pipelines, applying quantitative techniques, and ensuring governance and observability