Head of AI & Data Science Strategy

relx; Mexico; On-site; PHP 14,984,000 - 27,829,000; Full time

Benefits offered by this job

Flexible hours

Wellbeing initiatives

Parental leave

Study assistance

Sabbaticals

Country-specific benefits

Job summary

Elsevier leads AI and data science strategy across ML, NLP, search, and generative AI to deliver scalable knowledge-discovery systems. You will guide teams through the full lifecycle from experimentation to production, aligning work with product goals and customer needs.

You will influence senior stakeholders, shape roadmaps, and drive measurable outcomes across the organisation, building a culture of rigor, collaboration, and responsible AI.

Qualifications

• Significant experience in data science, AI/ML, NLP, information retrieval, or statistics.
• Hands-on delivery of AI-powered products and systems.
• Experience with LLMs, RAG, and knowledge-driven AI.
• Proven leadership of technical teams in product or research environments.
• Experience handling large datasets and scalable AI/ML systems.

Responsibilities

• Set AI and data science strategy across ML, NLP, search, and generative AI, aligned to goals.
• Lead and develop high-performing teams by coaching and building collaboration.
• Deliver AI systems from experimentation to production, including LLMs and knowledge-driven solutions.
• Establish evaluation frameworks, metrics, and responsible AI practices.
• Influence roadmaps across product, technology, and business with stakeholders.

Skills

Data science

AI/ML

NLP

Information retrieval

Statistics

Production AI

Tools

LLMs

RAG

Semantic search

Embeddings

Agentic workflows

Job description

Elsevier leads AI and data science strategy across ML, NLP, search, and generative AI to deliver scalable knowledge-discovery systems. You will guide teams through the full lifecycle from experimentation to production, aligning work with product goals and customer needs.

You will influence senior stakeholders, shape roadmaps, and drive measurable outcomes across the organisation, building a culture of rigor, collaboration, and responsible AI.