Developing end to end Machine Learning product that personalize experience for 14Million users

Speaker 1
Session Type: 30 minutes talk

Consumer behavior shift rapidly in recent years and deliver the most relevant content and products to the right person at the right time & place is the crucial factor for company to stay competitive. This session we will share how we develop end-to-end machine learning product to analyze data to better enhance user experience, improve engagement and increase business outcome for 14million users.

Speaker: Hafeez Nazri
Speaker Profile:

Graduated from UCL, UK in Msc. Computer Engineering, Hafeez heading team of Data Engineers and Data Executives to build, develop, design and engineer end-to-end data pipelines and data architecture, as well as perform data product integration.

Among achievements that has been achieved are:

  1. Productionalize and architect Media Prima’s own Recommendation Engine, which deployed on Malaysia’s biggest newsites, Berita Harian, News Straits Times & Harian Metro, as well as on Media Prima’s digital portal resulting 3x more engagement from users and saved OPEX of RM1 million.

  2. Developed and build Media Prima’s own Customer 360 Initiatives – building Enterprise Data Warehouse and Data Lake for Media Prima using Serverless Cloud Technology.

  3. Handling and processed petabytes of data daily in operational to support Media Prima’s Data Science Initiatives

  4. Developed and successfully implemented National Big Data Framework with MDEC as well as National Data Ocean Framework

  5. MDEC 1st Data Scientist in 2016 – has been working with GLCs, Private and Public sectors in building up BDA use cases