Data Scientist II (Statistical modelling) at TheNielsenCompany

At Nielsen, our goal is to build a better media future for all people. Our focus is on representing all audiences and understanding how they interact with content and advertising. As part of Nielsen’s Outcomes Measurement team you will be part of a data science team focused on building scalable solutions to answer the questions like: What was the return on investment for specific media spend? Which marketing type drove the highest return on investment? How do we measure the causal relationship between advertising and engagement/sales? How can we use data to help our clients plan for the future? Our Outcomes Measurement Data Science associates come from diverse disciplines that include business, economics, engineering, mathematics, operations research, physics and statistics.  These professionals drive innovation and insight through continual ideation, complex analyses and delivery of insights to our clients.  Because measurement is at the core of Nielsen’s business, our products have high visibility and make a direct impact on our clients. Nielsen's Data Science organization has an opportunity available for a Data Scientist II.  The ideal candidate must have expertise in leading the research and development of analytic solutions with a focus on mathematical modeling, statistical methods, and machine learning processes.  The candidate would also have the capacity to work in an agile development environment alongside software engineers, and a solid foundation in developing solutions for marketing, and advertising organizations. Responsibilities • Use and fit different mathematical and econometric models for explanatory purposes that deliver better decisions, and create high-quality data visualizations for internal and external purposes. • Research, design and implement analytic and mathematical approaches and algorithms to build scalable best of class web-based analytical solutions   • Design and test analytical modules for Nielsen modeling platforms • Partner with our Software Engineering department to build best-of-class web-based analytical solutions • Document and present methodology inside and outside the company