Lead AI Scientist — R&D, LLMs & ML Innovation

Mastercard; Bray (OK); Hybrid; USD 135,000 - 203,000; Full time

Job summary

Mastercard Foundry in Dublin is seeking a Lead Data Scientist to shape AI strategy across ML, DL and NLP, building scalable AI solutions for real-world use cases.

You will collaborate with cross‑functional teams across geographies, publish research papers and file patents, and mentor junior scientists while steering innovative product concepts.

The role emphasizes high‑impact delivery, strong coding practices, and the ability to translate business needs into robust data science programs.

Qualifications

• At least 7 years of relevant work experience in data science.
• Experience leading projects or small teams.
• Strong software engineering practices and code quality.
• Excellent communication, collaboration, and mentoring skills.
• Ability to work across geographies on R&D initiatives.
• Willingness to publish research and file patents where applicable.

Responsibilities

• Develop AI solutions using ML, DL and NLP techniques.
• Research new AI frameworks for POCs and products.
• Utilize LLMs for real-use cases and integrate with APIs.
• Contribute to requirements, standards and best practices.
• Coach junior team members and lead small projects.
• Communicate directions across groups and stakeholders.
• Publish research and file IDs/patents for concepts.
• Identify AI opportunities to enable business value.

Skills

Python

ML concepts

NLP concepts

SQL

Prompt engineering

LLMs

APIs

PySpark

Azure

Tools

FastAPI

GitHub

Bitbucket

PowerBI

Streamlit

Databricks

Job description

Mastercard Foundry in Dublin is seeking a Lead Data Scientist to shape AI strategy across ML, DL and NLP, building scalable AI solutions for real-world use cases.

You will collaborate with cross‑functional teams across geographies, publish research papers and file patents, and mentor junior scientists while steering innovative product concepts.

The role emphasizes high‑impact delivery, strong coding practices, and the ability to translate business needs into robust data science programs.