Quantitative Engineer Analyst

About the Role

This role is responsible for designing, developing, testing, and implementing common, reusable, and scalable software components, either domain-independent (generic data quality tools over billions of rows of data) or domain-specific (classification models for surveillance or testing frameworks for Global Markets processes). The position focuses on enabling Global Risk Management's data and analytical capabilities, working closely with modelers, risk managers, and technologists to understand the current state and design the future state of data and analytics.

Responsibilities

• Applies quantitative methods to develop capabilities that meet line of business, risk management, and regulatory requirements.
• Understands financial data: schemas, flow, size, data issues, data controls, etc.
• Builds performant big data pipelines.
• Uses programming skills and knowledge of software development lifecycle principles to deliver high-quality code for model and testing processes.
• Collaborates with key stakeholders across the Bank to understand modeling and testing business processes and requirements.
• Thinks outside the box of current industry standards to develop innovative approaches.
• Maintains and continuously enhances capabilities over time to respond to the changing nature of portfolios, economic conditions, and emerging risks.
• Applies critical thinking, sound judgment, and risk management principles to understand business processes, controls, and risks, influencing appropriate designs for technical solutions.
• Partners with process owners, data owners, Front Line Units, Technology teams, and other stakeholders to understand business requirements and build understanding of the firm’s processes and technology landscape.
• Leverages programming expertise, software development lifecycle (SDLC) principles, and AI development patterns to build and document scalable analytical solutions.
• Sources, validates, and analyzes data while designing scalable data pipelines and analytical solutions across large and complex datasets.
• Understands governance, security, observability, and auditability control requirements for AI-enabled solutions, including continuous monitoring of performance.

Qualifications

• Bachelor’s degree or above in fields including but not limited to: Mathematics, Computer Science, Statistics, Process and Mechanical Engineering, Operations Research, Data Science (or equivalent work experience).

Skills

• Analytical Thinking & Problem Solving: Applies structured thinking, quantitative analysis, and sound judgment to solve business, risk, data, and technology challenges.
• Communication & Stakeholder Management: Effectively communicates complex technical concepts to different audiences and builds strong partnerships across stakeholders.
• Software Engineering & AI Development: Demonstrated strong programming skills (e.g., Python), analytical and problem-solving abilities, digital fluency, and exposure to AI technologies, including large language models (LLMs), agentic AI concepts, or AI-assisted development tools.
• Data Engineering & Analytics: Experience working with structured and unstructured data, SQL, APIs, and databases to source, analyze, and integrate data while solving analytical problems.

Additional Skills

• Analytical Thinking
• Critical Thinking
• Oral Communications
• Prioritization
• Written Communications
• Attention to Detail
• Change Management
• Collaboration
• Presentation Skills

Shift: 1st shift (United States of America) | Hours Per Week: 40