Data Scientist (MLE/DAT)

The International R&D team within Data Science’s Audience Measurement organization focuses on applying and enhancing Nielsen’s highly successful products out in the marketplace for digital advertising and content measurement. In addition to defining and designing product methodologies, Measurement Scientists also design research studies to support and validate innovative measurement solutions, and lead the development and maintenance of new models to integrate different data sources This position will more focused on data engineering tasks still inside the R&D process

Responsibilities

• Participating, for data eng related task, into development, test, and refinement of data models using multiple types of data for various purposes such as imputation and data correction
• Participating into processes set-up for new algo according to methodologies specific goals Work with cross-functional teams to design, implement and test new audience measurement methodologies
• Document new methodologies and best practices
• Stay informed of new research and developments in the field

Skills Required

• This position requires a detail-oriented person who preferably has experience in data modeling research and who enjoys working in a fast-paced environment.
• Ability to problem-solve, work independently, and see the big picture are keys to success in this position. 
• University degree in Statistics, Computer Science, Applied Mathematics, Engineering, or equivalent demonstrated experience
• Solid experience with Python or similar languages, preferably in machine learnings context 
• Good communication skills (written and verbal)Proficiency in English, both written and spoken

Skills Desired:

• Knowledge about multivariate statistics (parametric/ non-parametric), trend analyses, sampling, automation Experience working on complex projects
• Experience with designing and validating measurement methodologies Master’s in statistics, economics, quantitative social sciences, operations research, or hard sciences 
• Experience working with global cross-functional teams of various sizes
• Experience with big data technologies