Curiosity, commitment, consistency and conscientiousness.

I tend to peg my work to these 4 values to ensure a certain level of standard and quality. By being curious, this motivates me to continue seeking for more knowledge and experience beyond my job scope. This generates new ideas and with commitment, will kickstart and materialise these ideas into actual projects. Consistency will ensure that these projects reach completion which helps to provide actionable impacts. Lastly, being conscientious means that the work carried out is done well and thoroughly.

My previous projects were more focused on data science related topics, ranging from machine learning (e.g. clustering and regressions) to causal inference (e.g. ab testing, quasi-experimental models etc.).

My current projects lean towards data engineering - preparing data for analytics reporting such as ETL/ELT, analytics engineering and working with streaming data.  Some tools involved in this work are Azure, alteryx and tableau.

I spent most of my university days mingling with research, prepared to take the academic career path. Unexpectedly upon graduation, I realised that I wanted to gain some experience  in the commercial settings before locking into academics. 

With zero commercial experience, and hence a severe lack of career prospects (graduating in COVID certainly did not help), I took up an internship with a local agritech startup where I had the opportunity to try out different types of work, which gave me a realisation that I enjoyed working with data. This event ultimately pivoted me into the data science track that I am in today.