Data Scientist

Job ID: 1274815 | Amazon Digital UK Limited

DESCRIPTION


THIS ROLE IS FOR A 12-MONTH FIXED-TERM CONTRACT

Amazon is seeking an outstanding Data Scientist on a 12 month fixed term contract to uncover key insights on how customers engage with Prime Video. As consumers increasingly consume digital video, we need to make agile decisions based on what content appeals most to our customers.

You will have the following responsibilities within the scope of our global Prime Video business:
- Support the analytical needs of the content acquisition management (CAM) team inclusive of statistical inferences, demand modelling, feature engineering and the bespoke evaluation of content licensing deals
- Develop, maintain and improve on our predictive models for gauging global video content demand
- Create new metrics and KPIs that effectively guide the business and deploy effective dashboards to surface them to senior leadership
- Ensure that the quality and timeliness of analytic deliverables meet CAM expectations

BASIC QUALIFICATIONS

· Bachelor's Degree
· Experience working as a Data Scientist
· Experience with data scripting languages (e.g. SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
- Previous experience with reporting and visualization using R/Shiny, Tableau or other similar data visualization and reporting packages
- Expertise in predictive modelling, including both parametric (e.g. logit/probit) and non-parametric (e.g. random forest, neural net) techniques

PREFERRED QUALIFICATIONS

- Master's degree in machine learning, operational research, computer science, statistics, applied mathematics or a related field; or equivalent experience
- Excellent verbal/written communication & data presentation skills, including an ability to effectively communicate with both business and technical teams
- Proven ability to work effectively in a cross-functional, fast paced environment
- Proven ability to understand and communicate issues at multiple levels, from validating and correcting junior staff detailed work to explaining the implications of analysis results to executives