Photo by Taryn Elliott from Pexels
Photo by Taryn Elliott from Pexels

In my first blog post, I initially planned to post my motivation for switching careers. However, the more I thought about what it means to be a ‘career-changer’, I realize that I’m not really changing the essence of what I do, but just my job title. So instead, I’m writing about how I’m going to continue doing what I’ve always done — just rather than doing my work from a boom lift or a rooftop, I’ll be in front of a computer.

Over the past 10 years, my job title has included engineer, research assistant, and lecturer, and of these three, engineer has been my main profession. However, whenever I was asked what I did, I would not reply “engineer” because engineer is too broad of a term(we’re amazing and can do anything…not really true, but I’ve got a lot of great stories over the years of what an engineer is capable of). So in lieu of saying “engineer”, I’d usually try to give a more detailed, but brief, description.

This would usually consist of a few words (e.g. consulting engineer or architectural engineer) or a sentence (e.g. “if structural engineers work on the bones of a building, I work on the skin of a building”). But my favorite description would be that “I diagnose and solve problems in building enclosures”. At the end of the day, a one-word summary of my job could have been problem-solver. Clients would approach my firm with a building that had various problems (I usually dealt with problems that related to moisture that entered through the building enclosure — including leaks and condensation). I would go to a building with my colleagues, observe the locations of leaks to figure out the extent of the problem(s), perform water testing to determine the source/cause of the leaks, design repairs, then often see contractors implement the repairs.

While being a data scientist will not require me to go on a rooftop to figure out how a building is leaking, it still requires a very similar process.

  1. Understand the extent of the problem: Just like observing the locations of leaks to better understand the initial problem — I need to clean/prepare data to gain an initial understanding of the data.
  2. Isolate the problem(s): Similar to performing water testing to isolate the leakage paths, I perform EDA to understand interesting characteristics in the data.
  3. Address the problem: In lieu of designing repairs to address building problems, I perform modeling to try to understand what’s going on in the data and see key influences or predict something.
  4. Implement a solution: Rather than seeing contractors implement repairs, I’ll be working with others to implement our data analysis process into production.

So am I really changing careers or just the medium in which I work? (In fact, I think what I’m really trading is my extensive wardrobe of jobsite clothing that can work in all types of weather and situations— including hard hat, work boots, water-resistant coats, and fleece-lined pants — for a consistent set of office-wear). I’m really excited for the chance to use my analytical skills that I’ve honed over the past ten years in a new environment that requires more quantitative analysis. But mostly, I’m excited to remain a problem-solver! And instead of fixing the world one leaky building at a time, I’ll be fixing the world one dataset at a time.

Photo by Andrea Piacquadio from Pexels

I’m a data scientist with a background in consulting, engineering, and teaching. I like to describe my thought process in a fun, clear, and thoughtful manner.