Senior Analyst - US Public Finance, Housing - New York, Denver, or Chicago

S&P Global•New York, NY

6d•Hybrid

About The Position

The Senior Analyst will join S&P Global Ratings’ Public Finance Housing team, which covers approximately 600 ratings across housing finance agencies, public housing authorities, and community development financial institutions in the United States. The team analyzes capital fund financings and federally enhanced housing issues, combining credit analysis and collaboration to deliver credit opinions on the affordable housing sector. The role leads end-to-end credit analysis and manages surveillance and updates for an assigned portfolio. It synthesizes performance, market signals, and peer context into risk insights, and uses large language model tools in analytical workflows with structured validation and documentation. The analyst communicates findings to clients, senior stakeholders, and rating committees; builds relationships with issuers and market participants; and helps coach junior team members. The position also supports controlled automation and AI-enabled tools, including their design, testing, and rollout, while helping establish boundaries between automated and human-led analytical work. The analyst is expected to follow methodology, confidentiality, and data governance requirements and escalate emerging issues with recommendations. Employees must work from an office at least two days per week. Candidates reaching the final interview stage must attend at least one in-person interview, ordinarily at their nearest S&P Global Ratings office. The role is limited to people with an indefinite right to work in the United States.

Requirements

Typically 3+ years of relevant experience in financial analysis, public finance, or affordable housing finance.
Demonstrated experience in affordable housing finance, such as loan underwriting, portfolio management, real estate development, or capital raising.
Understanding of affordable housing policies, financing structures, and funding programs, including low-income housing tax credits, Section 8 housing choice vouchers, and mortgage revenue bond programs.
Ability to analyze financial statements and credit risk and deliver high-quality outputs across multiple credits with limited oversight.
Practical experience embedding AI, large language models, or agentic workflows into analytical processes to improve productivity and insight.
Effective written and verbal communication skills, including the ability to explain complex analytical findings to senior stakeholders and rating committees.
Bachelor’s degree or equivalent required.
Indefinite right to work in the United States.

Nice To Haves

Master’s degree or professional certification, such as CFA.
Experience coaching or mentoring junior analysts in an analytical or financial services environment.
Experience contributing to scalable automation or AI workflows, including defining requirements, supporting testing, and enabling adoption.
Experience applying credit rating methodologies or public finance analytical frameworks in a structured credit assessment context.

Responsibilities

Coach junior team members on credit analysis, data discipline, and analytical tooling, promoting shared standards and responsible AI adoption.
Lead end-to-end credit analysis for assigned credits and deliver high-quality work on time across the housing finance portfolio.
Manage surveillance and updates for an assigned portfolio, synthesizing performance, market signals, and peer context into risk insights.
Use large language model tools in analytical workflows with structured validation and documentation.
Translate complex data, analysis, and research into clear narratives for clients, senior stakeholders, and rating committees.
Build effective relationships with issuers and market participants.
Adhere to methodology, confidentiality, and data governance requirements, and escalate emerging issues with options and recommendations.
Contribute to controlled automation workflows by supporting the design, testing, and rollout of AI-enabled tools and helping define boundaries between automated and human-led analytical processes.