Senior Data Scientist, USA-Philadephila or Mexico-Mexico City.

Are you excited by the opportunity to design advanced AI systems that accelerate scientific discovery and unlock knowledge at scale?
Would you enjoy building production-ready solutions using machine learning, NLP, and generative AI to create meaningful impact for researchers and professionals?

About our Team
Our integral team support products education electronic health records that introduce students to digital charting and prepare them to document care in today’s modern clinical environment. We have a very stable product that we’ve worked to get to and strive to maintain. Our team values trust, respect, collaboration, agility, and quality.

About the Role
In this role, you will design and deliver advanced AI, NLP, and generative AI solutions that power knowledge discovery and decision support. You will work with complex scientific data and apply modern machine learning and LLM-based approaches to build scalable, reliable systems with real user impact.



You will also collaborate across teams to turn complex challenges into practical, production-ready solutions.

Responsibilities
Design, build, and evaluate advanced AI/ML, NLP, and generative AI solutions for scientific and knowledge-discovery applications.
Develop LLM-powered workflows and retrieval-augmented generation (RAG) systems for search, summarization, question answering, and evidence-grounded insight generation.
Build intelligent retrieval, ranking, recommendation, and decision-support capabilities using modern orchestration frameworks and AI techniques.
Integrate scientific metadata, ontologies, taxonomies, and knowledge assets into scalable AI workflows.
Establish robust evaluation, experimentation, and monitoring frameworks to ensure quality, trust, performance, and reliability.
Write production-ready Python code and partner with engineering teams to deploy solutions at scale.
Provide technical leadership and mentoring to support high-quality

📌 Senior Data Scientist I (Ciudad de México)
🏢 Elsevier
📍 Ciudad de México