Data & Analytics
I’ve worked with data (aka Big Data) and analytics in a number of roles, and, after open source software, data became my new religion.
My first exposure to an analytics product was at zeebox (later renamed Beamly) where I was asked to take control of the Insights product. If you are not already familiar with zeebox, they were a second-screen application that customers used while they were watching TV.
The Insights product was originally built for a single partner, and it was unstable and produced unreliable data. Although I started with very little knowledge of working on data and analytics I studied up, asked the right questions and generally used my knowledge of how to build great products to create a product that worked for all of the zeebox content partners.
This is also where I learned a lot about collecting the right data, and how collecting data based on assumptions can send you down the wrong path of improving your product.
As the Cloud Product Manager for SwiftKey my goal was to take advantage of the core competencies of the company, natural language processing and machine learning, to create a product that used insights SwiftKey could extract from everything you write and serve it back to you in lots of other useful ways. I sought to turn what was a feature (backup and sync) into the core of the company by creating a service, that enabled an ecosystem of apps and partners.