About the Role:

Grade Level (for internal use):

The Team:

The Structured Finance (SF) team develops and maintains quantitative criteria, models, and tools that support credit rating and research across ABS, RMBS, CMBS, and structured credit. The team values technical rigor, timely delivery, and close collaboration with Methodologies and Ratings Technology to produce transparent, repeatable outputs used by global analysts.

What you stand to Gain:

• Deliver tools and analyses that directly support rating decisions and research across global teams.

• Build production-quality scripts, dashboards, and integrations while expanding practical experience with Python/R and SQL.

• Work with Methodologies, Ratings Technology, and Validation and mentor junior developers.

• Deepen practical knowledge of structured finance securitizations and credit risk modeling.

The Impact and Responsibilities:

Impact:

This role provides practical quantitative and technical support that improves the efficiency, transparency, and consistency of credit analyses and research. Your deliverables will be used by analysts and SMEs to inform rating decisions and maintain operational reliability of models and tools.

Responsibilities:

• Develop, maintain, and deploy user-focused quantitative tools, scripts, and dashboards to support credit analysts, following specifications from SMEs.

• Integrate models, data, and visualizations into reliable applications that support day‑to‑day analytical workflows.

• Analyze and synthesize datasets to produce actionable inputs, reports, and validation-ready outputs.

• Produce clear development documentation, test cases, and specifications; collaborate closely with Model and Criteria Validation to address feedback.

• Troubleshoot and resolve technical issues for non-routine problems, escalating complex or ambiguous matters to senior SMEs.

• Identify and implement incremental improvements to existing tools and processes that align with business needs.

• Coach and guide junior developers on technical tasks and best practices; support criteria projects by assisting with tool development, testing, and data gathering.

Compensation/Benefits Information (US Applicants Only) S&P Global states that the anticipated base salary range for this position is USD 101,000 - 122,000. Final base salary for this role will be based on the individual’s geographic location, as well as experience level, skill set, training, licenses, and certifications.

What We’re Looking For:

Basic Required Qualifications:

• Bachelor’s degree in Finance, Financial Engineering, Statistics, Quantitative Finance, Computer Science, Mathematics, Economics, or a related field.

• An S&P Global employee at this level would typically have 3–5 years+ years of extensive experience in quantitative modeling or software development supporting financial analysis.

• Hands‑on C++ experience is a core requirement.

• Proficiency in Python and/or R (experience with R Shiny is a plus); solid SQL skills, and familiarity with relational databases. Experience delivering reliable scripts, tools, or dashboards into production-like environments.

• Working knowledge of capital markets and structured finance concepts; able to apply domain knowledge to support model inputs and analyst workflows.

• Clear written and verbal communication; able to explain technical concepts to analysts and peers.

• Proven ability to work in cross-functional teams and follow direction from senior SMEs.

• All employees are required to work from the office a minimum of 2 days per week.

• We require all candidates who reach the final stage of our interview process to attend at least one in-person interview, which is ordinarily at your nearest S&P Global Ratings office. This must be completed before we can proceed to an offer.

Additional Preferred Qualifications:

• Master’s degree or advanced quantitative certification.

• Prior experience building interactive Shiny applications or similar dashboards.

• Familiarity with cloud environments and deploying analytical tools into production.

US Rig