When starting down the path of data after my post-doc, like a lot of other people, I worked on some personal projects to round out my skills and resume. One personal project, linked below, made it into an early edition of Data Science Weekly (www.datascienceweekly.org) and into the number one spot at datatau.net and r/datascience. The post also gain me a lot of attention, helping me land my first role as a data scientist. A few years later, the CEO of Mode used it as an example of an excellent data-science project (quora post). Even more important to me, I read a newspaper article years later that said that one of the SF neighborhoods noted as being undervalued in my blog post exhibited abnormally high growth of real-estate prices since then.
Why was this post successful and what can aspiring data-scientists learn from it? One major weakness that I often see in bootcamp projects is that they are purely technical. The aspiring data scientist cleans some data, applies an out-of-the-box algorithm it, and then maybe shows off the work in a web app or with a nice visualization. The problem is that these projects rarely demonstrate that you have enough technical strength to be a good hire based purely on your technical prowess (e.g., to be a machine-learning engineer). A boot-camp project isn’t really designed to demonstrate strength here either.
Data science projects that are successful, on the other hand, tend to demonstrate your ability to think through a vague problem and arrive at something useful. They show that you can use data-science methods – whether more technical ones like machine-learning models or simpler ones like data-munging and story telling – to elicit business value from data. They tell stories with data that make people want to act. They demonstrate creativity. They demonstrate that you will be thoughtful and rigorous in how you apply the data-science methods – that you don’t just copy and paste ideas or code from elsewhere, that you understand the nuances and trade-offs in your approaches, and that you are aware of business impact when you make decisions.
Best of luck to those working on breaking into the field!
