My LinkedIn profile describes me as a Software Engineer and Data Scientist. Based on my job history, the first half of that pair is probably more accurate, as I’ve only ever secured short-term contract gigs in data science. Having voluntarily moved out of an earlier career as a healthcare statistician, I was becoming vexed with my attempts to land a full-time data scientist position where I’m based, which is Singapore. I’ve seen some acquaintances, with only a Bachelor’s degree, readily secure positions while my Master’s in Medical Statistics and General Assembly certificate in Web Development did not seem to land the knockout blow that I hoped they would (two out of three in the Conway Venn diagram, or so I thought). My patience was also wearing thin with some of the “How I landed such-and-such role”-type self-congratulatory advice running rampant online which, after all, admitted a sample size of just 1.
This is a fascinating write up on the hiring trends of data scientists. Someone had posted this in a Telegram channel and I followed it from there. It is interesting because it shows the patterns of failure and a certain bias in the hiring ideas.
Long time back, thanks to my potential PI who ultimately rejected my application for a PhD, mentioned I didn’t write enough. This blog was a visceral reaction to it (last year, I wrote over 500,000+ words) and have written many more (especially discovering my ideas and interest in policy). The people who hire are more comfortable with the “references” and the “idea of birds of the same flock fly together”. A social media visibility helps in securing the precious grants too. There are many other failures that again have helped to discover several niches I never knew ever existed.
Cross-country migrations are tougher because of licensure restrictions. In my limited space, I have kindled the academic curiosity and developed several methodologies to track and consume information while generating a raft of ideas. Diversity of ideas and people is critical to ensure a rolling complex of practical ideas; much like the square pegs adjusting to fill up the round holes; persistence eventually shapes the holes too.
It is interesting to see the mix of people (and their backgrounds) being considered for the data jobs.
I can only surmise (and this remains my opinion) on the people getting in the medical field in other systems. There is a cross pollination and lateral career entries while we have a straightforward path; often defined as “end-of-the-road”. The local healthcare system rarely encourages any administrative entitlements and is limited to “managing the departments”. I have seen no groundbreaking policy wonks arising from my field. It is not a reflection on their clinical stature or their knowledge domains. However, as an impact on the greater common good, leadership or prioritising inputs on quality care usually falls on the wayside. These, of course, are strictly local socio-cultural issues and it has again prompted to explore this domain of “patient-centric engagements”.
I rarely indulge in self-reflection here. However, this linked post triggered a raft of ideas.
On a side note, if you feel you need to include a diversity of ideas in your workplace, I am available to move anywhere! I can be reached on “contact (at) myfastmail dot com”.