AI Data Scientist: Automation & LLM Solutions

S&P Global; Mexico; Hybrid; PHP 3,176,847 - 4,235,796; Full time

Benefits offered by this job

Health & Wellness

Flexible Downtime

Continuous Learning

Invest in Your Future

Family Friendly Perks

Beyond the Basics

Job summary

S&P Global is seeking an AI Data Scientist in a hybrid role based in Mexico City (onsite 2 days/week) or Colombia via remote work. The candidate will design automation workflows, build AI agents, and deploy LLM-based solutions with vector databases and orchestration tools.

Strong Python, data engineering, and ML experience are required. You’ll work with a cross-functional team to analyze data, create scalable pipelines, and drive business decisions from insights.

Qualifications

• 5+ years of programming experience with 3+ years of Python.
• 1+ years building and deploying LLM-based applications (RAG architectures).
• 1+ years workflow automation platform experience.
• 2+ years with relational or NoSQL databases.
• Bachelor’s degree in CS, Engineering, or related discipline.

Responsibilities

• Design workflow automation solutions to streamline operations for clients.
• Create AI-powered agents to automate tasks and improve efficiency.
• Build retrieval-augmented generation applications using vector DBs and orchestration frameworks.
• Collaborate with business teams to analyze data and build pipelines.
• Drive business decisions from data-informed insights.

Skills

Python

OOP programming

Design patterns

SOLID principles

Version control (Git)

LLM-based applications

Workflow automation

Data pipelines

Distributed systems

Education

Bachelor’s degree in Computer Science or related field

Tools

Vector databases

Orchestration frameworks

LLM operations/monitoring tools

Job description

S&P Global is seeking an AI Data Scientist in a hybrid role based in Mexico City (onsite 2 days/week) or Colombia via remote work. The candidate will design automation workflows, build AI agents, and deploy LLM-based solutions with vector databases and orchestration tools.

Strong Python, data engineering, and ML experience are required. You’ll work with a cross-functional team to analyze data, create scalable pipelines, and drive business decisions from insights.