With over 15 years of experience in software development, database technologies, data mining and analytics, Dr Lau Cher Han is a Data Scientist and full-stack developer with a wealth of experience and knowledge in big data analysis. He now teaches software engineering and big data topics at universities and conducts training programmes as well as offering consultancy services for various corporations in sectors such as travel, finance and tech startups.
Dr Lau Cher Han
What exactly does a data scientist do?
Our daily tasks involve gathering data, massaging data, cleaning data, modelling data, and creating visualisations. We also spend quite a significant amount of time on pre-processing data to ensure we get the highest quality of data before we move on to the actual tasks. We use these findings to answer questions that achieve specific business goals (such as reducing costs, increase productivity etc.). Then we have to communicate the results to clients or stakeholders.
As chief data scientist, I no longer to spend as much time on these as when I was a scientist. I still love to keep my hands busy and code sometimes. Now, I spend most of my time looking at the architecture, efficiency, and evaluate performance. I help to build and grow a team, and make sure that we map the right person to a position that he/she can perform best.
Could you tell us a bit about your background? How did you end up becoming a data scientist?
It was never my plan to become a data scientist. I got my Diploma in Computer and Networking Technology from Singapore Polytechnic. I was amazed by networking, routing and wanted to build my own LAN gaming facilities using hubs and crossover cables. I always thought that I would become a web developer. The real turning point was my bachelor’s degree. I picked the database major, where I learnt data mining and machine learning techniques. That eventually led me to a PhD in machine learning, focused on unstructured data.
Most data scientists still prefer to use Python / R for conventional data science tasks. With the recent rise in machine learning, libraries like Tensorflow are already available in JS (https://js.tensorflow.org/). Now we already build ML models in browsers.
Find out more here: www.cherhan.net