Automated Media Distribution Fulfillment and Business Intelligence Engine - ON-107
Preferred Disciplines and Level: Computer Science / Computer Engineering (Masters, PhD or PDF)
Company: Boat Rocker Digital
Project Length: 4-6 months with possiblity of extension
Desired start date: As soon as possible
Location: Toronto, Ontario
No. of Positions: 1
Preferences: Open to all applicants. U of T MScAC Preferred. Boat Rocker HQ is in Toronto. Language: English
About the Company:
Boat Rocker Media is a global entertainment company that creates, produces and distributes premium media content for all platforms and develops brands and IP for worldwide monetization. Boat Rocker Digital is building a toolset to allow Boat Rocker Media to increase the efficiency of its distribution efforts and provide insights for acquisition and future production.
Boat Rocker Digital is currently working on a cloud based solution for the storage, manipulation and delivery of high value video content to broadcasters worldwide.
Our goal is to use methods including machine learning and artificial intelligence to automate processes that currently require significant manual effort, analyse viewership data to expose insights for future content acquisition and production, and more deeply understand our buyers to better serve their needs.
- Create a tool to automatically create delivery files meeting buyer specifications
- Leverage big data analytics to better understand content within our catalogue
- Analyse buyer data – including viewship statistics and search history – to understand needs that are not met by our current catalogue
- Create a discovery engine which can provide suggestions to buyers for content within our catalogue based on prior purchases, passes and viewship data
- Create an auto-tiering and provisioning tool which optimizes our processing and storage costs
- To be developed
Expertise and Skills Needed:
- The project is built on Django and AngularJS1, so experience with these frameworks is valuable.
- Experience with Machine Learning, AI and Big Data preferred
For more info or to apply to this applied research position, please