Research Assistant, National‑Scale Credit Ratings

About the role

Grade Level (for internal use): 08 The Team: The IFR LATAM team assigns and surveils national ‑ scale credit ratings in Brazil, covering corporates and infrastructure issuers. You will work closely with senior analysts to support high ‑ quality analytical work that underpins S&P Global Ratings' mission of delivering transparent, independent credit opinions. This role fills a critical operational need created by recent internal mobility, ensuring continuity, efficiency, and stability across a complex portfolio that requires consistent analytical support, data management, and cross‑stakeholder coordination. You will also work within an environment increasingly shaped by AI‑enabled research workflows, automated data extraction, and digital tools that support modern credit analysis. The Impact: At S&P Global Ratings, every analytical contribution matters. Your work supports our reputation for integrity, transparency, and ratings excellence. Our ratings help investors measure and manage credit risk, enabling capital formation, infrastructure development, and economic growth. You will support analytical processes by preparing committee materials, maintaining databases, and assembling financial and technical information essential to rating activities. Your contributions directly reduce operational pressure on senior analysts, helping maintain turnaround times, analytical depth, and portfolio quality. You will also learn to leverage AI‑driven data tools, automation‑supported quality checks, and machine‑assisted research techniques that reflect current market norms in credit analysis.

Responsibilities

• Conduct research using both traditional sources and AI‑supported tools to prepare documents and presentations for rating committees.
• Support Senior Analysts throughout the analytical process across multiple sectors.
• Assist in collecting, validating, and analyzing financial, technical, and operational data.
• Maintain and update internal databases and analytical tools.
• Use automation‑enabled templates and data‑processing tools to improve efficiency and consistency in analytical outputs.
• Begin supporting simpler transactions to build foundational credit understanding.
• Collaborate with analysts to publish periodic thought ‑ leadership articles.
• Share fresh perspectives and contribute to reverse‑mentoring and collaborative learning.
• Comply with quality standards and internal compliance policies.
• Provide high levels of customer service and responsiveness.
• Build and maintain strong internal and external relationships.
• Demonstrate attention to detail, proactive support to the team, effective time management, adaptability, and curiosity.
• All employees must work from the office at least 2 days/week.

Requirements

• Bachelor's degree in Business Administration, Economics, Finance, Engineering, Mathematics, or a related field.
• Strong analytical skills and understanding of financial statement analysis.
• Ability to quickly absorb, analyze, and act on information with strong data proficiency.
• Openness to learning AI‑enabled research methods, automation tools, and data‑driven analytical techniques.
• Excellent verbal and written communication skills.
• Highly organized, able to multitask, manage competing priorities, and meet deadlines.
• Proficiency in MS Excel, Word, PowerPoint, and database applications.
• Fluency in English and Portuguese (Spanish is a plus).
• Please apply with an English CV; the recruiting process will be conducted in English.
• Basic Required Qualifications:
• An S&P Global employee at this level would typically have 0-1+ years of experience in analytical, financial, or research‑oriented work.
• Ability to determine a course of action based on clear guidelines.
• Strong attention to detail and ability to identify potential issues.
• Comfort using structured processes, templates, and AI‑supported tools to produce high‑quality outputs.
• Final‑stage candidates must attend one in‑person interview at your nearest S&P Global Ratings office before offer.
• Additional Preferred Qualifications:
• Coursework or internship experience in finance, economics, engineering, or data analysis.
• Familiarity with financial statements, credit concepts, or capital markets.
• Exposure to Python, R,

Your Match

How well this role fits your profile.

Company Intel

What employees say

Worked at spgi? Share your experience