Model Developer Senior Analyst - Structured Finance
External
Spgi · New York, NYPrepare for this interview
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About the role
Grade Level (for internal use): 11 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. The 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. You will play a significant role in initiatives to improve efficiencies in structured finance modeling while providing professional know-how to enhance the knowledge and skill base of the organization.
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 with particular focus on structured finance securitizations
- 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
- All employees are required to work from the office a minimum of 2 days per week
Requirements
- Basic Required Qualifications:
- An S&P Global employee at this level would typically have 3-5+ years of experience in quantitative modeling or software development supporting financial analysis
- Bachelor's degree in Finance, Financial Engineering, Statistics, Quantitative Finance, Computer Science, Mathematics, Economics, or a related field
- Hands-on C++ experience is a core requirement for this position
- Proficiency in quantitative programming languages such as Python and R (experience with R Shiny is preferred); solid SQL skills, and familiarity with relational databases
- Experience delivering reliable scripts, tools, or dashboards into production-like environments
- Working knowledge of structured finance securitizations and capital markets 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
- 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
- Experience with structured finance modeling methodologies and securitization analysis
- Compensation/Benefits Information:
- Right to Work Requirements:
- All successful candidates must be authorized to work in the country where this position is located. S&P Global will not sponsor work authorization for this position.
- About S&P Global Ratings
- At S&P Global Ratings, our analyst-driven credit ratings, research, and sustainable finance opinions provide critical insights that are essential to translating complexity into clar
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