In 6 months I’m done with my bachelor’s degree in Software Engineering.
I’m not sure about the exact direction I wish to push my career, but I know I’m very interested in health, building software & analyzing data.
It seems like everybody in this forum is Data scientists, so I thought this would be a great place to ask:
Does a Data Science job help you in your Quantified Self journey? Is it as interesting as analyzing your own data? Do you get inspired on the job on ways to explore your own data?
What are your thoughts on this?
First good luck on your remaining 6 months of undergrad studies.
It seems like everybody in this forum is Data scientists,
I am not sure if everyone is or has to be. I think people with IT backgrounds have built clever data collection and visualization systems, while people with more of a Data Science + Statistical background have utilized existing tools (Sheets, Excel etc) so they can focus on the main problem they are trying to solve.
Does a Data Science job help you in your Quantified Self journey?
Speaking from personal experience, I have learned a lot more about Data Science, Statistics and Machine Learning thanks to my QS journey. I may have acquired more book knowledge on those topics without QS, but QS forced me to ground the knowledge into practical and useful features and insights.
Is it as interesting as analyzing your own data?
Personally it is more motivating to analyze my QS data . I know exactly how the data was collected, the surrounding context and how this influences the interpretation of the final results. We don’t always have this level of understanding in the external datasets we download for analysis.
Do you get inspired on the job on ways to explore your own data?
Not sure I understood your question - are you saying whether analyzing my QS data inspires me to do more analysis or whether analyzing QS data inspires my day job functions? In any case yes on both
Paul Graham used to say one of the things that separates successful startups from the others is that their founders pick a problem they would like to solve for themselves. I think there is a lot of truth to this in the QS community - we each identify a QS problem that is interesting to us and we spend a lot of time in finding solutions to this problem. As part of this journey, we gain new knowledge, skill and experience including Data Science.
But the dashboards hardly ever analyze anything. become a statistician instead please.
I was trying to ask the other way around
So I mean whether your daytime job as a data scientist helps you gain knowledge & inspiration for ways to analyze your own QS data (I don’t mean whether analyzing your QS data helps you in your daytime job as a data scientist, even though that also is an interesting question)
My own background is more in biology before I turned towards bioinformatics and I’d say it goes both ways for me. I picked up a lot of data analysis/visualization skills by looking at my own data that I’ve collected through QS practices, particularly when I got started getting interested in more data-intensive things. But then it also happens the other way around where I end up using skills picked up in my academic research to look at my QS data.