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Global Head of Agentic Engineering

S&P Dow Jones Indices Technology is pioneering next-generation index technology through autonomous and semi-autonomous agents. The Global Head of Agentic Engineering will define the organization’s agentic engineering framework, lead the shift toward agent-driven software development and quality engineering, establish governance for agentic systems, and build a high-performing engineering team.

Vice President, Data Science

S&P Global provides data, technology, and insights that support financial markets and enterprise customers worldwide. The Vice President, Data Science will lead the AI/ML and applied data science roadmap, oversee the full lifecycle of production-grade models, and guide cross-functional teams in delivering scalable, explainable, and regulator-ready analytical solutions.

S&P Global is a global provider of essential intelligence, data, technology, and software solutions for financial markets and businesses. The Vice President, Data Science will lead the AI/ML and applied data science roadmap for Enterprise Solutions, overseeing production-grade models and the full model lifecycle while partnering with engineering, product, data platform, and business teams to deliver scalable, explainable, and regulator-ready solutions.

Machine Learning Engineer II

S&P Global's Kensho is an AI innovation hub focused on machine learning, natural language processing, data discovery, and generative AI solutions for business and financial applications. The Machine Learning Engineer II will develop and scale production-grade retrieval-augmented generation systems, including retrieval models, embedding infrastructure, vector search, and LLM pipelines. The role also partners with Product, Design, and ML Operations teams to deliver and maintain end-to-end machine learning systems.

Kensho, S&P Global’s hub for AI innovation and transformation, develops machine learning, natural language processing, and data discovery solutions for financial applications. The Machine Learning Engineer II will build and productionize agentic AI systems, develop retrieval methods, validate AI-generated outputs, and create scalable systems that connect financial data to actionable insights.