We are first and foremost problem solvers.

At the end of this course, I think that there are two things that have struck me the most that I hope would be as meaningful to the next batch as it was to me. This is especially relevant I believe to those who, like me, do not come from a very technical background and whose experience of data science is in its infancy.

The first memorable insight that I’ve taken away with me during my time in IDS is just how fast things are changing. Because we’ve had the privilege of having had talks about data privacy and AI ethics, I’ve come to realize that the industry as a whole has been focusing more on pushing the frontier of innovation in terms of the technical side of data. However, the side effect of this approach is that there are many things that have not been given their due attention. In terms of data privacy, there are issues coming up now that we never even had an idea of 5 or 10 years ago when, for example, social media started gaining a foothold in people’s lives. Who would have thought that social media, and a little company called Facebook, would be embroiled in the middle of a large controversy regarding the most powerful office in the world: thepresidencyof the United States? The effects of data are far-reaching, and it was very memorable to me to come to the realization that while sometimes we may think that we’re already breaching the limits of the cutting edge, we are just at the first step in realizing the power and effect, both positive and negative, that data science has. For us MSDS students, this is both an uplifting and sobering realization. Uplifting because we have a chance to become part of the select few individuals who have a say in guiding the future of data, but also sobering in the realization of the true weight of the responsibility that lies upon our shoulders.

The second thing that probably struck me the most was the realization of how “human” data actually is. Coming into this course, I fully expected this to be very technical and detail oriented; something that is quite out of my breadth. However, given the different things that we have learned in class, I’ve come to realize that the data science technical skills only form one aspect of a holistic data scientist. I believe it was Prof Chris who mentioned,in an info session I previously attended for MSDS,that “data is only good when you can communicateand articulateit.” My previous picture of a data scientist was of a person who sat in their office and just used “data” to “solve” problems. I now realize that a true data scientist is one who is in the middle of the action, someone who ties together the different aspects of a problem, whether it be the business side, finance, technical, or even HR side of things; and after taking all of these into consideration, aims to solve a problem using a data-driven approach. These, to me, are radically different notions: the notion of simply outputting data that will “magically” solve a problem, versus realizing that we are first and foremost problem solvers, whose main weapon and tool is the data driven approach that we bring into the fray. And I hope that the next batch would find this as exciting and as fulfilling as I do now.