Lead Data Scientist at NielsenIQ
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.
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
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.