In this Data Crunch episode 18, we talked to Mr. Nazmi Asri as he shares his insights and experience from building machine learning model, to deploying natural language processing (NLP), and his journey from being an IT graduate, to a data engineer, subsequently transitioning to become a data scientist.

Currently a data scientist in an established property group, En. Nazmi Asri works on machine learning projects, recommendation systems, understanding user behaviour – whether it’s rental or purchasing of a property.

At first, when he joined REA Group Asia, he requested to be assigned into a data engineering team (something he is familiar with) but he was assigned to become a data scientist instead.

From an ICT majoring in software engineering graduate to data scientist at current, Nazmi data science interest was sparked by reading articles about computer vision, facial recognition, AI-related applications – only to find out it is something he wants to pursue. Moreover, his final year project during his university days was into stock price prediction which had led him to apply deep learning and machine learning stuff without knowing it was an integral part of data science.

Fast forward till today, practising and dealing with data is part of his daily work. He also shared about his early days with an established airline company being a data scientist. In his previous role at the airline company, he helped to build customer data insights, to answer questions like “Is this a returning customer?”, “How frequently do they purchase a ticket?”, and “what destination is most demanded?” etc. basically to understand customer persona, user journey, and purchasing patterns.

Armed with a deep understanding about a customer’s behaviour, user history, ticket purchases, patterns and frequency, enables him to develop new ancillary products for a business or recommend products that a specific customer would highly likely to purchase. This data can also tell who would likely to buy more food based on the waiting time of each passenger.

Well, there’s a commonality that Mr Nazmi highlighted between the airline’s sector and the real estate sector which the data that he had his hands on – both falls under e-commerce. And once you’re able to understand how each business works and how they generate revenues, subsequently you’ll know what kind of products you can build for your company based on the data.  

Being a data engineer previously, Mr Nazmi also shared about the importance of understanding data pipelines, the architecture, and also the features that you’re able to gather from the data.

Watch and learn as he shares his insights and experience from building machine learning model, to deploying natural language processing (NLP), and his journey from being an IT graduate, to a data engineer, subsequently transitioning to become a data scientist.

If you enjoyed watching this, do share with us your thoughts in the comment section below.


If you are interested to learn more about programming, or if you aspire to become a data scientist, LEAD offers a complete data science course in Malaysia that is designed to equip you for a career in data science within 8 weeks.

What are you favourite programming languages for data science? Leave them in the comment section below.

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