As a Data Science mentor, I’ve always dealt with beginners having trouble in finding their first job. Even though we have a booming job market with so many positions for data professionals, these people keep complaining that they can’t even get to an interview.
For those more experienced, this is very atypical, we get several messages, I would say on a weekly basis at least. So, what’s wrong?
I would summarize the problem into three perspectives:
1.The job market doesn’t see you as a proper candidate: You are having trouble sending the message “I AM A DATA PROFESSIONAL” to the market.
2.Data Science related to the right keywords and project portfolio is not visible in your profile.
3. Recruiters can’t find you: This is such a simple problem to fix, that I keep repeating to my mentee over and over again. Most recruiting tools are automatized nowadays, so it’s usually not a person that is actually looking for you, but a robot (a program, to be more precise). You need to be found by it!
RIGHT, WHAT SHOULD I DO NOW?
TIP 1: HAVE A PORTFOLIO
Last year, I recruited two entry-level data scientists and I have to tell you that the market is booming on the demand side, but also on the supply. We received more than 50 resumes in less than a month, being a startup. Can you imagine what’s happening on the big companies? Can you imagine how many resumes they receive on a daily basis?
There’s too much competition, you need to stand out among other candidates. Besides, we have no idea how much you know regarding data science, machine learning, statistics, Python, and so on. Having a portfolio is the perfect strategy to stand out among so many resumes. It’s like you are right in front of us, programming and saying “Hey, this is everything I know, look at this DataViz, look at this model, etc, etc”.
Please, start your portfolio right now! It’s a must! If you have no idea what to do, here are a few links that might help you:
TIP 2: USE SOME KEYWORDS
As I mentioned in the intro, the search for job candidates is made by machines and you need to appear in their search. The simplest way of doing that is by using the correct keywords. If you have a strong knowledge in Python and in SQL, mention both tools in your Linkedin (and in your resume).
Take a look at your Linkedin right now, check if you mentioned all the programming languages you know, all the dataviz tools, the statistics techniques, the Machine Learning models and so on. Basically, I’d recommend you to have a headline containing two or three data terms you’re willing to work with and one or two languages (or tools) you have some proficiency. If you are only a beginner and feel insecure about this type of headline, you may add some word to express this level of knowledge (e.g.: “Data science enthusiast”). These are my choices for the headline and the “About” section:
TIP 3: THE LESS GENERIC, THE BETTER
Now, we have already shown the job market we know something regarding data science and the machines can find us in their search. However, we still need to convince the recruiter (and other stakeholders) we are problem solvers.
LET’S DO THIS!
I know some might think that only three tips won’t change much, but I guarantee you that you’ll at least double your chances of getting a data-related position by doing all of these. Keep improving your profile, becoming an attractive candidate for the job, and don’t stop studying. You’ll soon find what you want!
Mentor & Chief Data Scientist