[Hiring] Lead Data Scientist @NielsenIQ

Role Description

As a Lead Data Scientist within the Data Science Research team in the NIQ Product organization, you will drive definition and support of new products and methods development, and improvement initiatives. This position focuses on innovation in data processing methods for retail measurement and automation of existing statistical procedures.

• Define, plan and execute analyses regarding innovation initiatives, methodology development and improvement as well as process automation.
• Prototype solutions and support pilot programs for R&D purposes, including trend analyses, representation/sampling, bias reduction, indirect estimation, data integration, automation, and generalization.
• Test-driven development of scalable data processing applications.
• Deliver high quality documentation of new methodologies and best practices.
• Collaborate with experienced Developers, Data Scientists, and Technology engineers.
• Support various Operations team as main users of our solutions.
• Engage with stakeholders on scope, execution, data exchange, and outcomes for assigned projects.
• Participate in multiple projects simultaneously.

Qualifications

• Master degree in Statistics, Mathematics, Computer Science, Engineering or related fields with outstanding analytical expertise and strong technical skills.
• At least 5 years of relevant work experience.

Requirements

• Extensive experience in trend analyses, multivariate statistics (parametric/non-parametric), sampling, bias reduction, indirect estimation, data aggregation techniques, automation, and generalization.
• High proficiency in Python programming language including data analysis and statistical packages (Pandas, NumPy, Scikit-Learn). Good familiarity with Python standard library, especially unittest and argparse modules.
• Experience with Spark or other big data processing solutions.
• Experience in machine learning and GenAI / AgenticAI applications.
• Experience with cloud computing and storage (MS Azure preferred).
• Experience with Docker and Linux command line.
• Ability to quickly manipulate, analyze, and interpret large data sources.
• Strong communication/writing skills with good English (working in a remote team with a global footprint).

Benefits

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