Quantitative Engineer Analyst

About the Role

This job is responsible for obtaining an understanding of bank processes, including underlying data, flows, and controls, and designing and implementing technical solutions to enhance Global Risk Management’s (GRM) data, testing, and analytical capabilities.

Key Responsibilities

• Analytical Thinking & Risk Management: Apply critical thinking, sound judgment, and risk management principles to understand business processes, controls, and risks to influence appropriate designs for technical solutions to business problems.
• Stakeholder Engagement & Communication: Partner 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.
• Solution Development & Engineering: Leverage programming expertise, software development lifecycle (SDLC) principles, and AI development patterns to build and document scalable analytical solutions that support business objectives, regulatory requirements, and operational efficiency.
• Data Engineering & Analytics: Source, validate, and analyze data while designing scalable data pipelines and analytical solutions across large and complex datasets. Apply quantitative and analytical techniques to identify trends and assess risk.
• AI Governance & Operational Excellence: Understand governance, security, observability, and auditability control requirements for AI-enabled solutions, including continuous monitoring of performance. Develop understanding on how to drive process optimization and enhance solution effectiveness through testing, feedback loops, automation, and responsible AI adoption.

Requirements & Tech Stack

• Software Engineering & AI Development: Demonstrated strong programming skills (e.g., Python), analytical and problem-solving, digital fluency, and exposure to AI technologies, including large language models (LLMs), agentic AI concepts, or AI-assisted development tools through coursework, internships, personal projects, or professional experience.
• Data Engineering & Analytics: Experience working with structured and unstructured data, SQL, APIs, and databases to source, analyze, and integrate data while solving analytical problems.

Qualifications

• Bachelor’s degrees 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).
• Analytical Thinking
• Critical Thinking
• Oral Communications
• Prioritization
• Written Communications
• Attention to Detail
• Change Management
• Collaboration
• Presentation Skills