Senior Data Scientist at NIQ (Chicago, IL)
NielsenIQ Precima is a wholly-owned business unit of NielsenIQ. NielsenIQ invented the very concept of market share. Today, our data and insights continue to provide the essential foundation that make markets possible in the rapidly evolving world of commerce. Modern consumers have access to more choices via more channels than ever before.Job Description
As a Senior Data Scientist, you will support research and development projects. The associate will be accessing, analyzing, and interpreting customer-centric data to build advanced predictive models leveraging statistics, mathematics, and econometrics to support solutions such as Product Assortment Optimization, Retail Price Optimization, B2B Price Optimization, Personalized Marketing, Promo Effectiveness, Marketing Mix Optimization, and Floor Space Optimization. This role is an integral part of the Research and Development Department. You will have relevant B2B and retail industry experience and expert capabilities in statistical and econometric modeling in pricing, assortment, or marketing analytics applications. The candidate will understand the business needs of a B2B, retailer, or CPG client as well as the appropriate analytical approaches to pricing, assortment, and marketing problems encountered by these clients.
What you’ll do
Implement advanced statistical and econometric models of pricing, assortment or marketing. Provide analytical consulting on best practices and approaches.
Interpret, document, and present/communicate analytical results to multiple business disciplines, providing conclusions and recommendations based on customer-centric data. Be an internal expert in advanced capabilities
Work closely with AD/Advisor – Data Science to develop methodology and implement analysis and technology that enables more efficient pricing, assortment, and marketing/promotion decisions in support of product roadmaps
Take analytical objectives and define data requirements. Extract, clean, and transform customer and item-level data for purposes of analysis, modeling/segmentation, and reporting
Identify, develop and make recommendations for process improvements and best practices; own implementation of recommendations required.
We’re looking for people who have
Ph.D. preferred in Statistics, Operations Research, Mathematics, Economics, Econometrics, Industrial Engineering, and Computer Science
Retail or CPG Industry experience
Strong technical skills - SQL, Python, R, C++/C#
Demonstrated curiosity, initiative, and passion for the application of statistical sciences to address business challenges and learning new statistical/analytical methods
Team player with high energy and demonstrated initiative
Ability to translate analytical results into clear written and verbal communication to internal/external stakeholders
All your information will be kept confidential according to EEO guidelines.
NielsenIQ is a global measurement and data analytics company that provides the most complete and trusted view available of consumers and markets worldwide. We provide consumer packaged goods manufacturers/fast-moving consumer goods and retailers with accurate, actionable information and insights and a complete picture of the complex and changing marketplace that companies need to innovate and grow. Our approach marries proprietary NielsenIQ data with other data sources to help clients around the world understand what’s happening now, what’s happening next, and how to best act on this knowledge. We like to be in the middle of the action. That’s why you can find us at work in over 90 countries, covering more than 90% of the world’s population. For more information, visit www.niq.com.
NielsenIQ is committed to hiring and retaining a diverse workforce. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class.