Amazon is seeking an outstanding BIE Intern to uncover key insights on how consumers watch videos on Amazon. As consumers increasingly consume digital video, we need to make agile decisions based on what content appeals to our customers. As an Intern in the WW Digital Video team at Amazon, you will have the opportunity to work on one of the world's largest consumer data sets, influence the long term evolution of our analytics capability and build out the analytics team for our global expansion.
About this Internship: The intern will be work on one or more projects that will involve the following:
1. Using SQL to gather data on the consumption of video content from Prime Video Customers
2. Identifying critical business insights
3. Applying statistical techniques to build a model that will allow us to make informed content acquisition decisions
4. Integrating these insights into a tool (i.e. Tableau) and displaying the findings in a visually compelling way
5. Writing a document to outline findings and presenting it at the Content Analytics Research Review meeting
Sample past projects: using Nearest Neighbourhoods technique to identify similar titles; performing a Regression analysis to evaluate the impact of different variables on a title’s performance on Prime; creating a dashboard that shows performance metrics of video content over time.
The duration of the interview is one year.

Successful candidates will be able to demonstrate the following:
· Pursuing a degree in econometrics, statistics, operational research, optimization, data science, analytics, or other quantitative field.
· Some experience using relational databases and building SQL queries to interrogate TB-scale relational databases to build data sets and answer business questions.
· Familiarity in using tools such as SAS, R or Python to build predictive models using regressions and machine learning techniques.
· Strong interpersonal and communication skills. Must be able to explain technical concepts and analyses implications clearly to a wide audience, and be able to translate business objectives into actionable analyses.

· Familiar with theory and practice of information retrieval, relevance, machine learning, and data mining.
· Skilled at data visualization and presentation.
· Familiar with the core undergraduate curriculum of Computer Science.