Research Scientist (GenAI/LLM)

About the role

NielsenIQ is looking for a Research Scientist with a data-centric mindset to join its applied research and innovation team in Madrid. The role suits someone with a strong background in machine learning, deep learning, language models, GenAI, AgenticAI and process automation. You will analyze data, research the best techniques and develop, test, support and deliver proof of concepts that solve real-world, large-scale problems. The position is listed as hybrid.

Key responsibilities

• Develop and apply machine learning innovations by collaborating with team members and company stakeholders.
• Communicate requirements, results and conclusions accurately, clearly and persuasively.
• Carry out feasibility studies and analyze data to choose the most appropriate solution.
• Work on many data challenges while keeping ML solutions and source code simple, scalable, reproducible and maintainable.
• Develop and maintain data and software to high quality standards with minimal defects.
• Collaborate with technical fellows on integrating and deploying ML solutions.
• Contribute to team building, motivation and effective team relations.

Required profile

• Bachelor's degree in Computer Science, Statistics, Maths or an equivalent numerate discipline.
• Minimum of 2-5 years' experience with evidence in a related ML field.
• Desired: PhD or Masters in AI/ML with published papers.
• Desired: experience with large datasets, production-grade code, operationalizing ML solutions, tabular data, anomaly detection, time series forecasting and automated classification.
• Desired: experience in retail, consumer, ecommerce, business or FMCG products (NielsenIQ portfolio).
• Desired: experience with LLMs and Generative AI (prompt engineering, RAG).
• Desired: MLOps experience (MLFlow, Prefect) and deployment of AI/ML solutions to the cloud, especially Azure.

Required skills

• Hands-on expertise in Machine Learning, NLP, LLMs, GenAI, AgenticAI and data science.
• Prompt engineering, RAG, document processing and fraud detection.
• EDA analysis and hands-on experience with datasets, ML models and evaluations.
• Python, PyTorch, Git, pandas, Dask, Polars, scikit-learn, Hugging Face, Docker, Databricks.
• Analytical, problem-solving mindset and proactive attitude.
• Strong English communication skills and ability to meet deadlines.

What we offer

• Flexible working environment.
• Volunteer time off.
• LinkedIn Learning.
• Employee Assistance Program (EAP).