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Gold BlogThe Two Sides of Getting a Job as a Data Scientist

Are you a Data Scientist looking for a Job? Are you a Recruiter looking for a Data Scientist? If you answered yes or NO to this questions you need to read this.

By Favio Vázquez, BBVA Data & Analytics

Hello! This is a blog post I’ve been waiting a lot to write. Mostly because I needed to do my research and listen to what other people have to say about this.

I consider myself a Data Scientist, not a recruiter, but thanks to an amazing conversation I had with Amanda Voss and more recruiters in the area of Data Science and IT I have an idea now of both sides of the story: the DS looking for a job, and the recruiter looking for the best DS for a position.

Before starting, if you want to know more about my personal experience looking for a job as a Data Scientist read my blog: “How to get a job as a Data Scientist?


The Data Scientist side


So you are a Data Scientist, or you think you are getting closer to be one, and you started looking for a job in the area. My first suggestion: be patient! This is not an easy task, and maybe you will apply to hundreds of job before getting one.

Of course, it could be really easy and fast process, but in my experience this will take you at least (approx) 100 applications and several months.

Learn from each application, each rejection. When I started applying for jobs I had to deal with a lot of rejection. Something I was actually not prepared to. I think no one prepares you for rejection, but if you get something from this is, it’s ok! it’s normal and not personal!

Every rejection is a step on your way to success. It’s not easy to fit in every characteristic that the employer may want, or have the right experience, or maybe just cultural fit.

If you are lucky enough you will get an amazing recruiter that will let you know what happened and how you can improve for future interviews or processes. Recognizing your flaws and weaknesses is the beginning of getting better. This frustration you feel now, or you may feel use it to improve and get better every time.

Three Key points to have in mind about the process

  • Some people have no idea what Data Science is. So study the company you are applying for, see what their employees are doing, look for the way the communicate, their Facebook, LinkedIn, Twitter, talks and webinars. And see if they are doing something that interests you.
  • The recruiter is your best friend at the moment of interviews, they want to help you get in. So trust them, let them help you and ask questions!
  • People are generally more interested in how you solve problems and how you deal with some specific situations than your technical knowledge. Of course is important to write good quality code and have a full understanding of what you are doing, but there’s more than that.

Some advice to get a job as a Data Scientist

  • Be patient. You will apply for maybe hundreds of job before getting one (hopefully not).
  • Prepare. A lot. Not only studying important concepts, programming and answering business questions, also remember that you will be an important piece of the organization, you will deal with different people and situations, be ready to answer questions about how would you behave in different work situations.
  • Have a portfolio. If you are looking for a serious paid job in data science do some projects with real data. If you can post them on GitHub. Apart from Kaggle competitions, find something that you love or a problem you want to solve and use your knowledge to do it.
  • The recruiter is your friend. The people interviewing you too. They want you to get in the company, that’s a powerful advise that I remember everyday.
  • Ask people about what they do. I recommend that you follow Matthew Mayo post on “A day in the life of a Data Scientist” to have a better idea of what we do.
  • If you want an internship, have your academic skills on point.

Creating a Resume and a Life (what?) to get that job

Advice from Mark Meloon:

If you have something you want the reader or listener [interviewer] to know, you’d better put that up front in your message. For resumes, that means you lead with your strongest aspect. Maybe that’s your education. Maybe it’s your job experience.Don’t feel that you have to follow the order in that resume template you downloaded.

When an interviewer asks, “Tell me about yourself”, you don’t need to give them a chronological account of your life story. Start by telling them what your #1 strength is.

More from Mark:

You want to communicate your passion for the field? Do some personal projects. Contribute to open source. Start a blog. Heck, be active […] on LinkedIn.

Words are cheap; actions are what counts.

And in our competitive field, you want to avoid doing anything that will cause people to not take you seriously.

Advices from Kyle Mckiou:

Turn every bullet point on your resume into a mini story. You’ve probably already got a full page of text, and it’s probably cluttered with one-sentence junk that says “I did this” or “we did that.” Go ahead and delete half of that.

Now that you’ve freed up some space, start expanding on the remaining accomplishments.

Use the STAR format to give each bullet point context and to turn it into a detailed mini story with a resolution.

It’s better to have a few standout stories and accomplishment on your resume than a whole lot of “stuff.”

More from Kyle:

[when communicating with the recruiter] boil your communication down to 3–5 sentences that explain:

- Why you’re interested in the job and company

- Why your skills and background make you a good fit.

Also, be excited and passionate.

Outwork the competition.

Advices from Eric Weber:

Want to make an impact as a data scientist? Don’t only look at what is being done, but also what is NOT being done. Write out a list of the Top 5 things you could do to help the company. Then pitch your ideas.


1. It is hard to be self-critical. Examining what is not being done is hard but can push you outside the comfort zone of “let’s just keep things running like they are”.

2. Business moves fast. It can be hard to get out of the “get shit done” mentality when things seem to be on fire. But stepping away from that mentality provides a chance to be truly innovative.

3. You know the data really well. Very few others do. Understanding the potential of data is a data science job, not always something that management can always do.

4. Writing out a list forces you to track your thoughts over time. You commit it to paper and it will stick with you. In contrast, just thinking about something doesn’t always make it stick.

5. You must sell your ideas. Simply writing them is okay but without you pursuing your ideas to management, they won’t get off the ground. Pick your favorite one and start identifying its impact and ROI for the company.

Thinking, writing, and selling. Push yourself to do this regularly and you’ll find all sorts of new ideas to share.

Advices from Beau Walker:

Over the past ten years I’ve applied to 898 jobs on LinkedIn. I know this because LinkedIn keeps track. (Thanks for the reminder LinkedIn!)

This number doesn’t include the jobs I’ve applied to on other platforms or directly on employer sites. It also doesn’t include the numerous recruiter emails, InMails, and phone calls I’ve received.

Want to know how many jobs I’ve actually taken as a result of these activities?

Zero. Zilch. Cero. нуль. It’s true.

I’m 0–898 for jobs from LinkedIn! And I’ve never actually taken a job that I’ve found through a job board or recruiter.

I get asked a lot about how to find a job. And I talk a lot with people who are discouraged by the application process.

My advice? Consider alternative approaches to finding a job. In the past 10 years, every job I have taken has come from networking. The best jobs often do.

Advices from Vin Vashinta:

[…] when you’re in the mode of answering questions, it’s tough to start asking them. When you’re in the mode to impress, it’s tough to expect the same in return. Remember that hiring is a 2-way street.

Leave an interview with the team wanting more but also expect to leave the interview with the same desire yourself. Were YOU impressed? What did they do to make YOU feel welcome? You’ve put in work to get to where you are now. Gravitate towards those businesses that lift you up rather than diminish all you’ve achieved.

Great companies put in work to leave every candidate blown away, even the ones they don’t hire. Amazon is an excellent example of a company that has impressed me with their hiring process. I’ve had multiple dealings with their recruiters; always professional, quick to respond, & bringing roles that are good fits for my capabilities.

Advices from JT Kostman, PhD:

The problem most likely has to do with how you think about your resume.

Q: What is the job of the resume?

A: Wrong. It’s not to get you a job — or even an interview, or to the hiring manager. The job of the resume is to make it past the shredder. Period. Full stop.

Most […] peole who get your resume have absolutely no idea what we really do; they just have a list to check. They’re looking for keywords — not concepts. Most of the them are not going to be bothered with having to pan for gold. They’re going to give it less than a minute (literally) and move on to the next one on their pile.

Be honest: Is your resume so simple even some Bozo in HR/Recruiting can see how you would be a near ideal match? And is it about you? Or are you clearly showing (not telling) how you would benefit the hiring manager AND the company — including ensuring she can take fewer Tums every day? Are you connecting the dots for HR and drawing them a map?

Probably not.

Read all of that advices, and look for more. They are great. Some a little be hard to read, but they are true.

So what do I have to tell you to improve your life as a DS and also your resume? Here is my list:

  1. Be honest. Don’t undersell or oversell your self in your resume.
  2. Connect and be active in the data science community. Create blogs, share your knowledge, participate in open source projects.
  3. Be clear. Read your resume and ask yourself: is this how I want to be seeing?, be sure that you are putting the things that you think are the most important for you and the company you are applying for in the begining.
  4. Don’t send the same resume to every company. This is very close to the last point, and it’s a hard job. But believe me you’ll see results much faster. Analyze the company and create a resume specific for that position.
  5. Keep it short. They get thousands of resumes everyday, so they will only expend around 30–60 seconds reading yours. So be sure that you are putting there the things they want to see. Don’t put there stuff that is not relevant for the company.
  6. Be consistent. That means same font and style everywhere.
  7. Tell your story. Those bullets you see in your resume are you. So tell the story of your life in a way you and them will like it. If you are stronger on academic skills be sure to put that before the experience part, or vice versa.
  8. Ask the recruiter for advise before sending the resume.

More advice:

Creating a great data science resume


GitHub Is Your Resume Now