Job description

Job Description

As the world's largest research organization, NielsenIQ is powered by talented creative scientists. Our Data Scientist Leader come from diverse disciplines such as statistics, research methodology, mathematics, psychology, business, engineering, physics and demography. These professionals drive innovation, new product ideation, develops complex analysis and delivery of data insights to measure what consumers buy.


➢ Assist Sr Data Scientists on the deployment of the enhancements and new methodologies for new services

➢ Contribute to create new solutions use cases, proof of concept and prototypes by exploring diverse data sets using open source tools.

➢ Automate and develop solutions for existing processes.

➢ Document the enhancements, new methodologies applied locally and impact on the data

➢ Customize scripts according to local needs

➢ Assess quality, accuracy, completeness and statistical robustness of various data sources to embed in Nielsen product

➢ Collaborate with internal stakeholders (DBL, Product, GDDC, Technology and Ops team) to recommend improvements and deploy solutions

➢ Explain and communicate complex technical solutions to non-subject matter experts and the marketplace to address clients business problems.

About you

➢ Professionals with degrees in Maths, Data Science, Statistics, or related fields involving statistical analysis of large data sets.

➢ 0-3 years of experience in market research or relevant field.


➢ Essential soft skills qualifications

  • Passionate about innovation and technology.
  • Intellectual curiosity and persistence to find answers to questions.
  • Problem-Solving skills.
  • Eager to continuously learn and adapt to changing technologies and tools.
  • Good command of written and spoken English.
  • Good collaborative and interpersonal skills to communicate at all levels. (Preferred)
  • Ability to make decisions quickly and successfully manage multiple assignments concurrently in a high pressure environment(Preferred)
  • Ability to effectively convey complex concepts to non-experts.(Preferred).

➢ Analytical and Technical skills:

  • Deep knowledge of Statistics.
  • Good aptitude for data analysis and excellent critical thinking.
  • Knowledgeable in trend analysis, multivariate statistics, sampling, designing experiment, data aggregation techniques, automation and generalization.
  • Experienced with programming languages such as Python and R.
  • Knowledgeable with relational database management system (RDBMS) and knowledge of SQL.

Preferred/Desired Qualification

➢ Familiar with collaboration tools: Google Suit: Sheets, Slides, Google Data Studio. Atlassian: Git, Bitbucket, Confluence.

➢ Familiar with Machine Learning .

➢ Familiar with Cloud computing AWS, GCP, Microsoft Azure.

➢ Familiar with data visualization tools (e.g. Spotfire, Tableau) and mapping tools.

Additional Information

About NielsenIQ

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

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.

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