S&P; Enterprise Data OrganizationLead Data Scientist
The Team: As a member of the EDO, Collection Platforms & AI – Cognitive Engineering team you will work on building Gen AI-driven and ML-powered products and capabilities to power natural language understanding, data extraction, information retrieval and data sourcing solutions for S&P; Global. You will define AI strategy, mentor others, and drive production-ready AI products and pipelines while leading by example in a highly engaging work environment. You will work in a (truly) global team and be encouraged for thoughtful risk-taking and self-initiative.What's in it for you:
Be a part of a general company and build solutions at enterprise scale
Lead and grow a highly skilled, hands-on technical team (including mentoring junior data scientists)
Contribute to solving high-complexity, high-impact problems end-to-end
Architect and oversee production-ready pipelines from ideation to deploymentResponsibilities:
Define AI roadmap, tooling choices, and best practices for model building, prompt engineering, fine-tuning, and vector retrieval systems
Architect, develop and deploy large-scale ML and Gen AI-powered products and pipelines
Own all stages of the data science project lifecycle, including:
Identification and scoping of high-value data science and AI opportunities
Partnering with business leaders, domain experts, and end-users to gather requirements and align on success metrics
Evaluation, interpretation, and communication of results to executive stakeholders
Lead exploratory data analysis, proof-of-concepts, model benchmarking, and validation experiments for both ML and Gen AI approaches
Establish and enforce coding standards, perform code reviews, and optimize data science workflows
Drive deployment, monitoring, and scaling strategies for models in production (including both ML and Gen AI services)
Mentor and guide junior data scientists; foster a culture of continuous learning and innovation
Manage stakeholders across functions to ensure alignment and timely deliveryTechnical Requirements:
Hands-on experience with large language models (e.g., Open AI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
Expert proficiency in Python (Num Py, Pandas, Spa Cy, scikit-learn, Py Torch/TF 2, Hugging Face Transformers)
Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
Strong grasp of statistics, probability, and the mathematics underpinning modern AI
Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
Proven experience on at least one end-to-end Gen AI or advanced NLP project: custom NER, table extraction via LLMs, Q&A; systems, summarization pipelines, OCR integrations, or GNN solutions
Familiarity with orchestration and deployment tools: Airflow, Redis, Flask/Django/Fast API, SQL, R-Shiny/Dash/Streamlit
Openness to evaluate and adopt emerging technologies and programming languages as needed
Master's or Ph. D. in Computer Science, Statistics, Mathematics, or related field (minimum Bachelor's)
6+ years of relevant experience in Data Science/AI, with at least 2 years in a leadership or technical lead role
Prior experience in the Economics/Financial industry, especially with market-intelligence or risk analytics products
Public contributions or demos on Git Hub, Kaggle, Stack Overflow, technical blogs, or publicationsLocation: Mexico City, Santa Fe (2 days a week onsite)