GenAI/LLM Research Scientist - Data-Driven ML

NielsenIQ; Madrid; On-site; EUR 70,000 - 110,000; Full time

Benefits offered by this job

Flexible working environment

Volunteer time off

LinkedIn Learning

Employee-Assistance-Program (EAP)

Job summary

NielsenIQ in Madrid is seeking a Research Scientist with a data-centric mindset to join our applied research and innovation team. You will analyze data, research techniques, and develop, test, and deliver proofs of concept to solve real-world, large-scale problems.

The role emphasizes ML, NLP, GenAI, AgenticAI, and process automation, with collaboration across stakeholders and a strong focus on scalable, maintainable solutions.

Qualifications

• Bachelor's degree in CS/Stats/Math or equivalent numerate discipline.
• Hands-on expertise in ML, NLP, LLMs, GenAI and data science.
• Understanding and practice of prompt engineering, RAG, document processing and fraud detection.
• EDA with datasets, ML models and evaluations.
• Proficiency in Python, PyTorch, Git, pandas, dask, polars, sklearn, huggingface, docker, databricks.
• Strong English communication and ability to meet deadlines.
• 2–5 years' experience in related ML field.

Responsibilities

• Develop and apply ML innovations with team and stakeholders.
• Communicate results clearly and effectively to non-technical audiences.
• Conduct feasibility studies and analyze data to select solutions.
• Handle multiple data challenges with scalable, reproducible ML solutions.
• Develop and maintain high-quality code and documentation.
• Collaborate on integration and deployment of ML solutions.

Skills

Machine Learning

NLP

LLMs

GenAI

AgenticAI

Prompt engineering

Data analysis

Python

Pytorch

Git

Pandas

Docker

Databricks

Education

Bachelor's degree in Computer Science/Statistics/Math

PhD/Masters in AI/ML (preferred)

Tools

HuggingFace

Scikit-learn

Dask

Polars

Azure

Job description

NielsenIQ in Madrid is seeking a Research Scientist with a data-centric mindset to join our applied research and innovation team. You will analyze data, research techniques, and develop, test, and deliver proofs of concept to solve real-world, large-scale problems.

The role emphasizes ML, NLP, GenAI, AgenticAI, and process automation, with collaboration across stakeholders and a strong focus on scalable, maintainable solutions.