Job Board

S&P Global's Enterprise Solutions Technology team is seeking a Data Science leader to own the AI/ML roadmap and lead the design, development, and production operation of high-rigor analytical and machine learning systems across a complex, regulated financial-services estate — spanning lending, corporate actions, tax, regulatory reporting, and public and private markets.

• Define the AI/ML strategy and own the full model lifecycle: problem definition, feature engineering, back-testing, deployment, monitoring, drift detection, and retraining
• Build production-grade models for anomaly detection, variance analysis, forecasting, and market and behavioral signals — comparable in rigor to fraud, risk, or surveillance systems
• Work closely with engineering, data platform, and product teams; step in on complex or high-risk analytical problems and when models degrade in production
• Design explainable models suitable for regulated environments, combining statistical models, ML, semantic models, and rules-based logic as appropriate
• 20+ years of experience with analytics, data science, or ML systems in production, with significant experience in financial services or similarly regulated domains

S&P Global's Agentic AI Platform & ML Engineering team is seeking a Principal ML Engineer to architect and deliver production-scale LLM, Generative AI, and Agentic AI systems — driving S&P's AI transformation both internally and for customers. This is a senior individual contributor role at the intersection of cutting-edge research and real-world product delivery.

• Architect and deploy production LLM systems including RAG pipelines, multi-agent orchestration, tool-use, memory management, and enterprise guardrails using frameworks such as LangChain, LlamaIndex, and LangGraph
• Build cloud-native AI infrastructure with GPU cluster management, auto-scaling inference endpoints, and vector databases on AWS, GCP, or Azure (Bedrock, Vertex AI, Azure OpenAI, vLLM)
• Design production-grade Python APIs and backend systems (FastAPI, gRPC), own end-to-end performance and reliability, and embed AI workloads into CI/CD pipelines with Docker and Kubernetes
• Implement MLOps/LLMOps practices including prompt versioning, model governance, and observability; advise leadership on AI strategy, build-vs-buy decisions, and responsible AI policies
• 10+ years of progressive experience, with 8+ years in ML engineering or data science; expert Python, distributed systems, and cloud platform depth required

S&P Global is seeking a Lead Identity Engineer to architect its next-generation API security and authorization platforms — including the Model Context Protocol (MCP) Gateway that serves as the secure bridge between enterprise data and AI agents. This role is central to enabling safe, compliant adoption of Generative AI across S&P's digital supply chain.

• Architect and govern the MCP Gateway, implementing Fine-Grained Authorization (FGA) and context-aware policies to protect critical data sources against unauthorized AI access
• Lead API security and authorization platform design with deep expertise in OAuth 2.0, OpenID Connect, and enterprise API gateway technologies (Kong, Apigee, AWS API Gateway, or Azure API Management)
• Build high-performance APIs and microservices in Java or Python; integrate security controls into CI/CD pipelines with Jenkins, GitHub Actions, or GitLab
• Work with enterprise identity providers (Okta, Microsoft Entra ID) and apply IAM principles to the high-velocity, complex access patterns of AI agents
• 8+ years of software engineering experience, with 5+ years focused on API security, IAM, or gateway implementations; MCP knowledge strongly preferred

GA Intelligence develops cutting-edge software solutions that transform raw data into actionable intelligence, supporting real-time global situational awareness and battle management for tens of thousands of users across the DoD and Intelligence Community. As a Lead Data Scientist, you'll drive the design and delivery of high-performance analytical solutions, set rigorous standards, and lead a cross-functional team of data scientists and software engineers.

• Lead development of machine learning models and analytics for mission-critical national security applications, including tracking, activity detection, and automatic target recognition
• Architect and scale high-performance analytical systems handling hundreds of thousands of observations per minute across global sensor networks
• Collaborate with software engineers, mission engineers, and product owners to deliver streaming and batch analytics for strategic and tactical decision-making
• Represent GA Intelligence as a senior technical expert with customers, partners, and engineering teams, including across DoD and IC networks
• Hire, mentor, and grow a team of data scientists and software engineers
• Requires 9–14+ years of data science experience (depending on degree level) and the ability to obtain and maintain a DoD security clearance

GA Intelligence builds best-in-class, globally focused situational awareness capabilities that process petabytes of data from hundreds of streaming sources in near real time, applying state-of-the-art machine learning to extract features and fuse data across multiple phenomenologies — giving end users a live, rich view of objects in the sky, on the sea, and on the ground. As a Data Scientist on the core product team, you'll help shape the next generation of these capabilities.

• Design, develop, and deploy statistical and machine learning models using state-of-the-art approaches for real-time situational awareness
• Integrate analytics into systems that consolidate and analyze diverse, unstructured data sources to generate actionable insights
• Build data visualizations and communicate findings to product, service, and business stakeholders
• Identify opportunities to improve products and customer processes through machine learning
• Requires 1–5+ years of data science experience (depending on degree level); active TS/SCI clearance with CI Poly preferred
• Preferred: experience with deep reinforcement learning, geospatial analytics, simulation environments (gym, Unity, Unreal), and DoD/IC mission sets

Rotational crafts bespoke AI solutions tailored to clients' unique needs. As a Machine Learning Engineer, you'll design and deploy production ML systems, fine-tune language and computer vision models, and collaborate closely with data engineers and software developers — working on a wide range of technical challenges in a collaborative, growth-oriented environment.

• Design, develop, and deploy ML models using open source libraries such as HuggingFace, PyTorch, and TensorFlow, with a focus on NLP and/or computer vision
• Integrate models into production systems alongside data engineers and software developers; conduct rigorous experimentation and evaluation for accuracy, efficiency, and scalability
• Participate in sprint planning, daily standups, and synchronous and asynchronous code reviews; communicate technical feasibility and solutions to stakeholders
• Stay current with ML and AI research and incorporate cutting-edge techniques into client solutions
• Proficiency in Python and ML fundamentals required; degrees and specific credentials are not — practical experience and a passion for continuous learning are what matter

Rotational crafts bespoke AI solutions tailored to clients' unique needs. As a Data Engineer, you'll design and maintain the scalable data infrastructure that powers AI model development and deployment — building ETL pipelines, optimizing databases, and contributing to open source projects in a collaborative, curiosity-driven environment.

• Design, build, deploy, and maintain scalable data pipelines and ETL systems ingesting from heterogeneous sources; implement data security and privacy measures
• Optimize databases and queries for performance; work with PostgreSQL, MongoDB, Neo4j, Prometheus, and others using SQL, Cypher, PromQL, and more
• Implement libraries to interact with APIs and remote services; monitor and operate pipelines using observability tooling; respond to bugs and outages
• Contribute to open source projects — code, pull request reviews, documentation, and mentorship; participate in sprint planning, standups, and code reviews
• Proficiency in Python required; Go and/or JavaScript a plus; experience with cloud platforms (AWS, GCP, Azure), Docker, Kubernetes, and concurrency patterns preferred