A nontraditional data science job candidate recently asked about how to become a data scientist when their education background was in marketing and social media.
They already knew that they were competing against people with computer science and/or math degrees so were curious about two specific things:
- Will they not be employable as a data scientist without any actual CS/math degree?
- In order to become employable as a data scientist, what topics/languages should they learn first
Before answering our friend’s questions about whether they need a degree or what topics/languages they should learn, it’s helpful to step back to look at the bigger question: How do I get hired as a data scientist with a nontraditional background?
We’ll cover the answer to this particular question in this article, and then we’ll cover the specific answers to our friend’s questions in other articles
There are two ways to get hired into a company - the human resources path and the hiring manager path. The human resources path is going through a recruiter, through a company’s hiring page, through a company’s hiring system, or through an internship application. The hiring manager path is going through the hiring manager or one of their employees.
The human resources path usually involves dealing with lots of people before you get to talk to someone who ultimately has to approve your being hired. Where as the hiring manager path usually involves dealing directly with the person or group of people whom will ultimately approve you being hired as well as the person or group of people whom you will ultimately work with.
For a data science job candidate like our friend with the marketing degree, the best way to get a data science job with a masters in marketing is the hiring manager path. This is because the traditional human resources path would mostly involve getting filtered out of the candidate pool because our friend does not have a degree in mathematics or computer science.
So now that they know that they have to go through the hiring manager path, we advised the candidate to take stock of what they already knew and what businesses they already knew. Here’s what they came up with that we thought was relevant:
- Social Media
- Social Media Agencies
- [Industry they cover retracted]
Though those are relatively broad, it at least gives the candidate a starting point. Because they will already have a good idea of the business side of those four areas, we suggested that they look at companies that have data in those verticals that are hiring or already have established data science teams.
So as a first answer in the conversation with this candidate, we suggested they focus on those types of firms when approaching and considering data science positions. Further, we suggested that they focus on finding hiring managers / people on the teams that are doing data science to understand what it is that they are doing. Obviously, they will need the skills to properly do and succeed at a data science job, though as a non-traditional candidate we thought this was the right first step in the right direction.
Similarly, if you are a candidate from a nontraditional background, we suggest as a first step the following:
- Make a list of what industries you know
- Make a list of what organizations you know within those industries
- Find data science teams and/or hiring managers at those organizations
- Realize that your best bet for getting a data science job will be through the hiring manager path and not the human resources path