Within Nielsen’s core business of Global Watch, the Data Science Digital Product Team drives development and support of our cross-platform measurement product Total Content Ratings (TCR) that provides clients with a view of what content people view on Live and streaming TV, computers, smartphones, tablets, and other devices. As part of the project, the intern will focus on initiatives targeting methodology innovations that will positively impact TCR data quality. The role would center on evaluating different statistical strategies to deal with sample sizes in TCR data sources. The intern will get an opportunity to investigate statistical modeling and machine learning techniques that might be more accurate and stable than the current approach.
1. Understand the challenges underlying measurement of content viewing across TV and digital devices
2. Conduct research on methodology innovations using statistical techniques ranging from classical modeling to machine learning and AI
3. Analyze data to determine the best methodological strategy for the product’s needs
4. Design a methodology that can be implemented and automated in production, and validate it by running analysis coded in Python
5. Summarize and present your research findings to stakeholders, both technical and nontechnical
Undergraduate/ Graduate students majoring in Statistics, Math, Data Science, or related fields
Anticipated graduation in 2019/2020 (preferably in May)
Proficient in Python and SQL
Familiarity with working using Machine Learning techniques.
Strong communication skills, clear and concise written documentation skills
Naturally curious, detail oriented, passionate about data quality and statistical methods, ability to drive a project to completion
Availability full-time June - August 2019 in NYC