North America / United States / IL / Chicago /

Technology & Engineering

#: 743999738254990 / REF2752O



Job Description

Our Data Science teams help to provide NielsenIQ’s clients with the most complete understanding of the market and its consumers. With a footprint in over 100 countries across the globe, our expansive data and measurement capabilities provide market context and confidence. We are constantly innovating to keep pace with emerging market trends and the increasingly diverse, demanding, and connected consumer.

As a Lead Data Scientist, you will work with a Data Science team dedicated to the development of E-Commerce products, a new way to measure how people shop online. We are looking for someone to improve our E-Commerce offerings in the US and then eventually work on other E-Commerce initiatives in North American markets. 

You will serve as the key Data Science contact for US internal teams – in particular with Client Service, Technology, Operations, and Product Leadership. You will use your technical, mathematical, and analytical skills to define and lead Global and regional innovation initiatives, methodology development,  KPI development & implementation, standards, and best practices.  

About you

Ideally, you should have knowledge of consumer panel behavior, experience with unmanaged panels, and developing strategies for improving panel engagement, improving data quality, and influencing panelists. You should have a passion for consumer-sourced data!

What you’ll do

  • Evaluate current E-Commerce Product methodologies to identify opportunities for enhancement

  • Deliver on methodology enhancements to E-Commerce products, improving overall quality from client perspective

  • Serve as Data Science’s chief point of contact for US eCommerce solutions. Present findings with stakeholders and support the resolution

  • Prototype as well as support pilot programs to drive innovation.  

 We’re looking for people who have

  • 3-5 years of experience in Consumer Insights/ Shopper Insights/ Data Analytics 

  • Experienced in high-level programming languages (Python or R)

  • Knowledge in SQL, working with queries and large-scale databases

  • Hands-on experience working with insights around consumer transaction data/ POS data/ Shopper panels / Panel and Data management

  • Excellent statistical and logic skills. Experience in trend analysis, multivariate statistics (parametric/ non-parametric), sampling, bias reduction, indirect estimation, data aggregation techniques, data fusion, and model validation techniques

  • Experience implementing weighting and projection schema (e.g. RIM weighting) and clustering techniques (e.g. K-means, nearest-neighbour, random forests)

  • Strong communication and collaboration skills

  • Ability to effectively convey complex concepts to non-experts

  • Business acumen, the ability to link client's needs with the business

  • Ability to manage multiple projects simultaneously 

  • Minimum B.S. or Master’s Degree or Doctorate degree in Statistics, Data Science, Actuarial Sciences, Operations Research, or Econometrics