Senior Analyst - Structured Finance

As a Rating Analyst, you assess credit risk in structured finance and fund structures, translating portfolio signals into actionable insights. You work with cross‑functional teams to deliver consistent, governance‑driven analysis that informs issuers and investors. You engage with market participants to communicate S&P Global’s analytical expertise and risk views. You’ll contribute to building scalable, standards‑led processes and responsibly apply AI in analytical workflows for better decisions.

• Health & Wellness: Health care coverage designed for the mind and body
• Flexible Downtime: Generous time off
• Continuous Learning: Access to learning resources
• Invest in Your Future: Competitive pay, retirement planning, and education support
• Family Friendly Perks: Perks for partners and children
• Beyond the Basics: Perks such as retail discounts and referral incentives

• Execute end‑to‑end credit analysis and surveillance for structuredFinance credits, synthesizing performance signals into decision‑useful insights
• Prepare inputs and outputs, reconcile metrics, and document assumptions to ensure methodological adherence
• Engage with external stakeholders, translating data into client‑ready narratives to support market engagement
• Ensure adherence to data governance and governance requirements, advocating responsible AI usage and governance updates

• 1+ years of relevant experience in structured finance, credit analysis, or related field
• Demonstrated credit, financial, and risk analysis skills with forward‑looking views
• Strong written and verbal communication; ability to synthesize analysis into clear narratives
• Willingness to learn and apply AI tools, LLMs, and automation technologies
• Fluent English; German proficiency preferred
• Bachelor's degree or equivalent; CFA or advanced degree valued (preferred)
• Experience analyzing ABS, RMBS, or corporate securitizations (preferred)

• Effective communication
• Collaborative mindset
• Analytical rigor
• AI tools and large language models
• Automation technologies and workflows
• Data governance and methodological discipline