Structured Finance Analytics Analyst - Methodology & AI Solutions

DBRS Morningstar's Structured Finance Analytics group (SFA) supports the analytics lifecycle through predictive models and analytical tools, software maintenance, regulatory requests, cash flow analytics, data pipelines, performance insights, infrastructure, and automation. Within SFA, the Solutions team coordinates project flow, develops analytical methodologies, performs quantitative consulting and investigations, coordinates model and tool review with the Methodology Review Function, and supports AI-enabled solutions across Global Structured Finance (GSF). The Analyst will support the Head of Solutions across methodology development, AI initiatives, analytical investigations, and executive presentations. The role suits an intellectually curious, highly organized candidate who can work across analytics, technology, and business functions. Advanced coding expertise is not required, but candidates should be comfortable with data analysis and technical environments. Experience using generative AI or AI-assisted coding tools to prototype solutions, automate workflows, or test ideas is especially valuable. We cover many topics, and you are expected to quickly learn nuances of the credit analysis industry. ## Job Responsibilities - Support the design, documentation, testing, and maintenance of bespoke analytical methodologies. - Help coordinate, test, document, and drive adoption of AI-enabled solutions across GSF. - Use generative AI and AI-assisted development tools to prototype practical solutions and automate repeatable tasks with appropriate review and oversight. - Create executive-ready dashboards, visualizations, presentations, and quantitative analyses. - Partner across analytical, technology, business, and governance functions to improve processes and decision-making. ## Qualifications - Bachelor's degree in an analytical discipline and 0-3 years of relevant professional experience. - Strong organization, project management, analytical problem-solving, communication, and attention to detail. - Ability to balance multiple priorities and build effective relationships across technical and business teams. - Curiosity about AI, data-driven decision-making, structured finance, analytical methodologies, and software development lifecycles. - Familiarity with Python, SQL, or other coding languages a plus. - Hands-on use of generative AI, AI-assisted coding, prompt design, low-code/no-code, or workflow automation tools a plus. - Exposure to project management tools like Jira or Asana a plus. - Exposure to financial services, credit ratings, structured finance, risk analytics, quantitative modeling, or cross-functional AI projects a plus.