The primary responsibilities include optimizing and standardizing data science and machine learning solutions at large scale, supporting end-to-end analytical approaches, working with Point of Sale data, bridging gaps between data science and engineering teams, and representing MLEOps expertise at conferences and workshops.
The role requires a Master or Bachelor's degree in computer science or engineering, with expert skills in Python, machine learning ecosystems, database environments, and statistical methodologies. Candidates should have 5+ years of work experience, solid understanding of machine learning architectures, production-level code quality, and expertise in statistical techniques like survey statistics, econometric modeling, or causal inference.
NielsenIQ offers a flexible working environment with continuous learning opportunities, professional development, volunteer time off, LinkedIn Learning, and an Employee Assistance Program. The company provides a chance to work in an international team, gain experience across different product teams, and contribute to cutting-edge consumer intelligence solutions.
