Principal Research Scientist - AI & Data Science

About the role

NielsenIQ is looking for a Principal Research Scientist in AI and Data Science to join an interdisciplinary, global R&D team in Bogota. The team researches, develops and deploys new statistical, machine learning and AI methodologies to improve products and processes within the Data Science organization. You will combine advanced technologies with strong analytical skills to deliver R&D tasks.

Key responsibilities

• Research and develop new methodologies, research directions, prototype solutions and quantify their improvement using rigorous scientific methods in the ML/AI space.
• Own every phase of an R&D project or process improvement, from conceptualization and design to prototyping, documentation, deployment and monitoring.
• Collaborate with experienced teams in operations, technology, other data scientists and internal stakeholders throughout the project.
• Deliver high-quality, academic publication-level documentation of new methodologies and best practices.
• Work with stakeholders on objectives, scope, execution, data exchange and outcomes, and contribute to several projects at once.

Required profile

• Ph.D. in Data Science, Mathematics, Statistics, Engineering, Computer Science or a related field, with outstanding analytical expertise and strong technical skills.
• At least 7 years of relevant experience.
• Domain expert knowledge across programming, software engineering, UI/UX, multivariate statistics (parametric and non-parametric), machine learning, deep learning and agentic AI, trend and time-series analysis, and sampling theory.
• Critical and innovative thinking, with a focus on experimentation and hypothesis testing.
• Strong communication, presentation and collaboration skills in English, with a record of written materials and public presentations such as papers, conferences, patents, tutorials or Substack articles.
• A continuous learner willing to experiment with new technologies and tools.

Required skills

• High proficiency in Python (without AI assistance) and large-scale databases (SQL, Hadoop, pySpark).
• Statistical packages (Pandas, NumPy, Scikit-Learn) and unit testing.
• Experience with AzureML, DataBricks and CI/CD best practices (Docker, Unix, AKS).
• Comfortable working in a virtual environment and with Git (GitHub), including pull requests and conflict resolution.

What we offer

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