Principal Research Scientist - AI & Data Science

About the role

NIQ is looking for a Principal Research Scientist in AI and Data Science to work with an interdisciplinary, global R&D team that develops and deploys new statistical, machine learning and AI methodologies to enhance NIQ products and processes. The role suits someone who enjoys research and R&D and wants to use advanced technologies to improve products and processes.

Key responsibilities

• Research and develop new methodologies, research directions, prototype solutions and quantify their improvements using rigorous scientific methods in the ML/AI space
• Own all phases of an R&D project or process improvement, from conceptualization and design to prototyping, documentation, deployment and monitoring
• Collaborate with operations, technology teams, other data scientists and internal stakeholders throughout the project lifecycle
• Produce 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 strong analytical expertise and 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 blogs
• A willingness to keep learning and adopt new technologies

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 (Docker, Unix, AKS)
• Git (GitHub) workflow, including pull requests and conflict resolution

What we offer

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