Director – Esoteric ABS, Denver, CO or Toronto

S&P Global•Toronto, ON

12h•$150,000 - $210,000•Hybrid

About The Position

The Director on S&P Global Ratings’ Esoteric ABS team leads credit analysis across a portfolio of complex structured finance transactions backed by non-traditional collateral, including transportation assets, data centers, triple-net leases, whole business securitizations, timeshare facilities, and private equity structures. The role delivers independent, forward-looking credit opinions and market insights that help issuers and investors understand performance trends, issuance conditions, and evolving credit risks. This senior leadership position combines analytical authority, team development, and stakeholder engagement. The Director serves as a subject matter expert and escalation point, leads rating committee discussions, guides analysts, and shapes the adoption of modern analytical practices while maintaining rigorous human judgment, accountability, and analytical independence. The role also maintains disciplined portfolio risk oversight and ensures AI and automated outputs are transparent, explainable, and compliant with governance and regulatory standards. The position is based in Denver, Colorado, or Toronto. Employees must work from the office at least two days per week, and final-stage candidates must attend at least one in-person interview at an S&P Global Ratings office. The position is eligible for an annual incentive plan and additional S&P Global benefits. The anticipated base salary range is $150,000–$210,000 USD for US candidates or $140,000–$239,000 CAD for Canadian candidates, subject to the stated factors and applicable compensation details.

Requirements

Typically 10 or more years of relevant experience in structured finance, securitization, credit analysis, capital markets, or related fields.
Experience mentoring colleagues and/or managing small teams, with the ability to foster accountability, continuous improvement, and responsible AI adoption.
Strong credit expertise and ability to deliver high-quality analytical output at pace across a complex, multi-asset portfolio.
Practical experience using generative AI, data, and advanced analytics tools to improve research, monitoring, drafting, and workflow efficiency, with strong validation and analytical discipline.
Strong relationship management skills and proactive stakeholder engagement, communicating complex analytical insights clearly and credibly while maintaining analytical independence.
Bachelor’s degree or equivalent required.
Final-stage candidates must attend at least one in-person interview before an offer can proceed.
Employees are required to work from the office a minimum of two days per week.

Nice To Haves

Experience partnering with Data, Technology, Compliance, and Methodology teams to identify workflow improvements and scale best practices.
Master’s degree or professional certification, such as CFA, is highly valued.
Academic backgrounds beyond traditional finance disciplines are welcomed when they support innovative and critical thinking.

Responsibilities

Lead, coach, and develop analysts, building credit expertise and responsible use of generative AI, advanced analytics, and automation tools.
Drive adoption of modern analytical practices across monitoring, drafting, research, and workflow execution while maintaining human judgment and accountability.
Lead end-to-end credit and capital markets analysis across an assigned portfolio of esoteric asset classes, supporting ratings, surveillance, and rating committee discussions.
Serve as a subject matter expert on cash flow analysis, transaction structures, and ratings criteria.
Lead rating committee discussions, review third-party model outputs, provide analytical guidance to junior team members, and act as an escalation point for complex analytical matters.
Build and maintain relationships with issuers, investors, bankers, legal counsel, and other market participants.
Contribute to thought leadership through commentaries, webinars, podcasts, and external market engagement.
Communicate complex, data-informed analysis clearly and credibly while maintaining analytical independence and objectivity.
Oversee portfolio risk, identify emerging risks early, and escalate them appropriately.
Apply rigorous controls to AI and automated outputs to ensure transparency, explainability, and adherence to governance and regulatory standards.