How Did You Get Into Data Science?
Asking someone how they got into their profession often leads to the same conversation for each respective field. Ask a lawyer and they will all tell you they went to law school. Ask an Accountant and they will all tell you they studied accounting and finance. Ask a doctor and they will all tell you they went to med school. Ask a data scientist and you will hear a different story from each person.
From former physicists to sociologists to financial analysts to college drop outs, data scientists have come from every origin imaginable. Being in a new and exciting field will do that. How new is data science? Well, six years ago, the words, “statistics” and “big data”, were googled more than “machine learning” or “data science”. Now, that trend has reversed dramatically. How dramatic is it? Six years ago, I was looking for jobs using key words such as “statistics” or “statistician”. Now, any statistician would be a fool if they didn’t change their LinkedIn job title from “Statistician” to “Data Scientist”.
This has resulted in the fun, common ice breaker among data professionals, “how did you get into data science?”. When I was asked this question, I used to give a general, modest answer of how I liked math and was fortunate to fall forward into the field of data science. But what does that mean? Only recently, did I dive into my past a little more and remember that my origin story was a little more interesting than what appears at the surface.
It all started six years ago when I was working for the federal government and attending graduate school for economics. At the time, I had never heard of SQL or python. R was briefly mentioned to me once by an undergrad professor who treated programming as a secondary priority to learning statistics by hand and paper.
So what happened?
Would you believe me if I said that it all started from a random email that was sent to the bullshit email section in my Outlook? You know, the emails that people will often skim or skip completely because they have much higher priorities to worry about. Today, these sections are called “Other”, “Promotions”, or automatically filtered as unimportant (irony at its finest*). A random decision to spend 30 seconds skimming through this list of unimportant emails had a huge impact on my future career path. It fast-forwarded my likely transition into data science by years. It vastly improved my career options. If I were bold, I might even claim that it increased my net worth by thousands of dollars. Talk about a good ROI.
So what was in this email?
It was an opportunity to apply for a temporary job assignment within the federal government where they trained you in python and basic data science skills. After the training, there would be an opportunity to work on your own data science project and integrate it into the organization. I immediately applied. Was accepted. Fell in love with python and data science. And the rest is history.
Next time you meet a data professional ask how they got into data science. I guarantee that you will hear some interesting origin stories.**
*Ironically, data science/machine learning was likely the root cause in sorting one of the most important emails of my life into the unimportant email section.
**This applies more often to individuals who entered the field prior to 2020. The path to becoming a data scientist/professional is becoming more standardized as tons of graduate programs and bootcamps have popped up over the past 5 years.