Data Scientist, Data Science and Solution (Retail ...

Job description

Company Description


Job Description

Are you passionate about Data Science? At NielsenIQ, our people are proud to work with some of the world’s leading Fortune 100s on challenging, cutting-edge, data driven solutions, powered by technology, and people. Our team has an exciting opportunity to work with a team of Data Scientists/Machine Learning Engineers that support Walmart, the largest retailers in the U.S. If you consider yourself an innovator, diplomat, and influencer of change and strategy in the field of Data Science & Analytics this is a great opportunity to apply those skills work with a team at one of our premier clients.


  • Develop insights from data into products using advanced statistical and machine learning methods
  • Build and validate predictive models with advanced machine learning techniques and tools to drive business value, interpret and present modeling and analytical results to non-technical audience
  • Support on-going project execution and partner with client service team to facilitate the execution of projects and developing new business at existing clients.
  • Use Hive, Python, SQL, to write, validate and maintain code to support research and data analyses.
  • Work with large datasets of respondent level, log file, or transactional level.
  • Develop processes/code to extract data across a multitude of platforms.
  • Diagnose issues and areas of improvement regarding QC, efficiency and accuracy of data preparation.
  • Build and convey impactful insights drawing from multiple data sources and modeling.
  • Maintain codebase for newly developed systems (e.g. Git/Bitbucket).
  • Create process documentation to ensure clear and consistent operating procedures.
  • Explain technical subject matter to non-technical audiences, both internal and external.
  • Provide accurate and timely data analysis and methodology support focused on internal and external client requests.


  • Bachelor’s Degree or equivalent work experience in Computer Science, Information Science, or related disciplines. Master’s degree preferred.
  • Proficient programming in Python or R.
  • Comfortable with Hive or SQL to prepare, aggregate, or transform data for analysis.
  • Highly passionate about data with a problem-solving mindset.
  • Previous market research, CPG, or retail experience preferred.
  • Proven success as a team player in a professional environment.
  • Demonstrates strong interpersonal, communication, and presentation skills.

Strongly Preferred Skills

  • Experience in simplifying/converting business problems into ML problems.
  • Hands-on experience with modern machine learning libraries, frameworks, and technologies
  • Ability to leverage critical thinking and analytical skills to improve business outcomes
  • Excellent written and verbal communication skill
  • Self-motivated with ability to set priorities and mentor others in a performance driven environment.

Additional Information

All your information will be kept confidential according to EEO guidelines.

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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