About the role

Lead AI Researcher enhancing AI expertise related to credit risk for S&P Global. Collaborate with stakeholders on AI advancements and develop innovative solutions in a hybrid work environment.

Responsibilities

Serve as a domain expert on Generative and Agentic AI for Credit Solutions.
Attain fluency in AI applications, including the use of open-source and internal tools, to enhance AI expertise within Credit Solutions.
Utilize internal and external AI applications offered by S&P Global to support credit risk analysis and decision-making.
Closely monitor emerging technologies, industry adoption, and associated risks, including strengths, limitations, and regulatory guidelines concerning Gen-AI in credit risk.
Develop and test new credit risk use cases utilizing data and AI applications within S&P Global across multiple platforms, including data wrangling and cross-referencing.
Analyze quantitative and qualitative data from various content sets linked to credit ratings within S&P Global to understand their contributions to credit risk surveillance and risk management workflows.
Collaborate with the Credit Solutions Thought Leadership team to develop and work on internal applications within a sandbox environment.
Author thought leadership content independently and represent S&P Global at webinars and conferences, focusing on AI advancements in credit risk management.

Master’s or Ph.D. degree in Data Science, Statistics, Quantitative Finance, Artificial Intelligence, or a related quantitative/computational field.
5-10 years of relevant experience in AI/ML, quantitative roles, or data science.
Ph.D. graduates in a statistics/data science/quant finance discipline from an internationally accredited university with hands-on experience in Gen-AI projects may be considered with 0-5 years of experience.
Proficient in Python, R, and SQL.
Experience in accessing data via feeds, cloud, or REST API preferred.
Familiarity with GenAI frameworks (e.g., RAG, Agentic AI) and libraries including Hugging Face, TensorFlow, PyTorch, or Scikit-learn preferred.
Prior experience in developing predictive analytics, data wrangling of structured and unstructured data, Natural Language Processing, or other emerging AI and automation use cases in financial services.
Some knowledge of testing and validating AI models using techniques such as cross-validation, A/B testing, and performance metrics.
Strong communication skills with a proven ability to solve problems and engage effectively across functions.
Self-starter with a proactive mindset, capable of working independently across multiple groups and stakeholders.

Health & Wellness: Health care coverage designed for the mind and body.
Flexible Downtime: Generous time off helps keep you energized for your time on.
Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.
Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.
Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families.
Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.