Unconventional Strategies to Land Your Next Job in The Data Industry

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In the past year, Glen, a data analyst student at Dataquest.io, has spent hundreds of hours learning programming techniques on the platform, working on exercises, and finishing module projects. He hopes to land a job soon in the data industry. He is switching into data because he recently heard that data science is the sexiest job of the 21Ist century. Some of his friends who are also students at Dataquest recommended the platform to him because it has well-written contents that are easy to follow and assimilate coupled with excellent and responsive customer service.

Now, Glen thinks he is ready to apply for jobs. Job boards like Indeed.com and Glassdoor.com come to his mind. However, he says to himself: “I think I ought to prepare my resume and LinkedIn profile first.”

If you ask HR coaches and experts in the labor market, there is nothing wrong with Glen’s plan. But there is one very significant shortcoming - every job seeker seems to use the same strategy without success.

The job market scene is changing so fast so much that if you continue to use the same methods, you will also continue to get the same old results. The labor market is saturated. The Covid-19 pandemic has not made it any better as many workers have been laid-off.

So the big question is: how can Glen, and as an extension you, land your next job? The purpose of this article is to answer this from my research by breaking the process into simple bits so that as you read, you can stop at any point to implement the proven suggestions.

Ask yourself questions?

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Questions like: Why do I want this job?

It might seem easy to answer. This will help you to be selective as to what job to apply for instead of wasting your time every day applying for whatever vacancy you find listed.

To make my point clearer, are you seeking a job to look for extra cash to pay some bills? Want to work remotely from home for health reasons? Switch to another industry? Want to work in a more formal and challenging environment? Wish to expand or grow your career? Etc.

The fact is that every company has a culture it stands for and the type of employees they are looking for. Dataquest, for example, is a full remote platform that is passionate about data education. This will determine how you design your resume and which job you apply for. Else, you will not scale through to the interview stage and even if you do get the job, you might soon become frustrated at work because you’re not the company’s type of employee.

Find the companies that may be interested in your services

Many vacancies never get opened to public view. This is why you need to do your research. But how do you go about it? Here are some ways to do so:

  1. Do a simple Google search

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If you don’t know where to start from or how to start, a Google search of the type of company you’ll love to work with will be quite helpful. For example, if I am interested in real estate startups in San Francisco, I could search that on Google and get a list of such.

2. Use LinkedIn

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LinkedIn isn’t just a social media site but one of the best places to find a job and make lasting career connections.

After logging in and ensuring your profile is ready (you may want to read how to do so on the Dataquest community or ask for a profile review from the student’s career moderators), hit the job section and type in the role and location. You can try the remote option if that’s what you’re looking for. This should return a list of vacancies.

From here, you will see the company’s names that you are searching for and the range of employees they have. Next, after clicking the company, check the right navigation plane of your window, you will find the “Pages also viewed” section. This is a list of similar companies in the same business niche.

Why should you be interested in companies that haven’t put up job openings?

Because there is a hidden job market that only becomes accessible to those who are within the circles of decision-makers of any company. For example, someone may be due for a promotion soon- leaving a space that you could fit into. Employees get fired; others resign or even die. You might be the right replacement if you act smartly and fast.

3. Alexa search

Alexa.com ranks sites based on website traffic. So if you have a company in mind in the niche you’ll love to work in, type in the official site of the company to find out about their top competitors. This gives you a list of sites in the same business that may need your services.

4. Create an organised list of companies/contacts

At this point, you ought to have a list of preferred companies. I suggest you compile up to 25-30 companies on a CSV file.

Next thing you need now is the names of employees in the companies that you should connect with. These persons will be those that can give you first-hand information or vouch for you when you don’t know anything going on. They may be those who you will be reporting to when hired or someone who has something in common with you e.g. a data analyst if you are applying for that role, alumni of your high school, university, or Dataquest.

To get the names of these persons, you may want to check the official site of each company and check on their team section or hit LinkedIn again, search the name of the organization, then click on “people” to reveal their employees. You could filter your search result (click the “all filters “button on top) by location (if you’re dealing with a multinational company or an organization with several branches within the same country), service categories, etc. When you get the desired people, copy and paste their names and job titles into the CSV file where you already have the list of your companies.

Send cold emails to set up an interview

If you notice something in common with someone on your list, say both of you live in the same neighborhood or you’re both alumni of the same school, it’s advantageous to schedule an interview with the person. You could use a cold message if you’re a premium user of LinkedIn or take advantage of the “add a note” option while connecting if you use the free version. Below is an example of a cold message.

Hello James Corton,

My name is Eboigbe Ikponmwosa and I am a data analyst experienced in real estate. I noticed we’re both alumni of Dataquest, have an interest in real estate, and also live within the same neighborhood. I was wondering if you could spare me a few minutes on a weekend to buy you a cup of coffee while we discuss what it’s like working as a data analyst at Ideal Homes corp.

Thanks for your consideration.

There are some things you may have noticed in the message and they are very important.

  • The message is personalized to one individual. There’s power in using someone’s full name and job title as it arouses the interest of the receiver in the message.
  • The sender’s name is also present
  • The sender maintains a common ground by stating areas of interest and similar background
  • The sender may have 1-year experience in working with data. That isn’t impressive so he chooses to write that he is experienced in an area in which the receiver works
  • The sender isn’t begging for a job or asking if there’s an opening. This is very important. PLEASE DO NOT ASK FOR THE JOB. Using this strategy is like wooing a beautiful lady. You don’t want to be pushy else you’ll miss the opportunity.
  • Instead of asking for a favor, the sender offers something (a cup of coffee and an interesting discussion). People love talking about themselves and what they like engaging in.

NOTE: This is cold mail. Do not expect everyone to reply to you. However, you may be lucky enough to get a 10% response rate if you draft the message well.

What then should you discuss when you eventually meet?

Ask questions like:

  • What are the top skills required for day-to-day work as a data analyst in your company?
  • What type of employees works in your company?
  • What is the working environment like?
  • Which other departments in the company will a data analyst be required to work with?
  • What’s a real-life example of a problem I may be told to solve as a data analyst?
  • Is there any other person in the company that I could speak with?

If you decide to leave out the interview aspect and go straight to connecting with the persons in your contact, be sure to do your research about the organization very well. Is there anything that makes them stand out from their competitors? Are they innovative in their business style? If the answer is yes, ensure to include that in your message. Here is a hypothetical example below:

Hello, James Corton

My name is Eboigbe Ikponmwosa and I am a data analyst experienced in real estate. I recently researched your organization, Ideal Homes corp. and must say I was attracted to your style of operation. Having an easy investment option using a phone app is amazing. This ensures that real estate investment is not left to the high-class earners only. It was as thrilling to find out about your investor community where all investors can ask questions and relate with each other.

As a data analyst, I believe your organization can soar higher if you use data analysis to find the right homes at the right prices for your customers.

If you’d like, I could explain more through writing or a virtual meeting with you. I will also love to know more about your company.


Again, this message is personalized, direct, and I’m not asking for the job directly rather, I’m offering a helping hand.

Final steps

After getting the connections you want, what next? You think it’s time to write your resume now?

You’re close but not yet! You need a targeted resume - something the recruiting person will scan through, keep aside and say, ”This is exactly what we’re looking for”.

How do you get there by the way? It’s easy.

  1. Get your project portfolio and LinkedIn ready


Recruiters want to be sure that you are qualified for the job. These days, companies want smart employees who can teach them and ultimately make money for them, not someone who they will spend money on to train.

With your research, your task now is to make sure the LinkedIn profile you’ve is in line with the company’s mission and operation. Dataquest has an excellent wiki resource on Dataquest community about how to prepare your LinkedIn so I won’t be talking about that.

Another thing you should look at and possibly improve on is your project portfolio on GitHub. The recruiters for technical roles expect you to have worked on projects or have published something similar to what you will be doing when hired. Your work should also reflect how you can work with a team. With the job description research handy, you will have an idea of what type of projects you should work on. This is very important for anyone with no job experience. Again, you could contact the Dataquest students’ moderator team to review your projects on GitHub and how you ought to organize your repositories.

  1. Prepare your resume


Now it’s time to talk about your resume. I’ll not be writing much about this because the Dataquest team has written a well-researched and helpful blog post about getting your data science resume right. However, there’s a need for you to apply for a job with a targeted resume - one that will immediately catch the attention of the recruiter and be the best fit for what they are looking for.

Ladders.com found out from research they did that recruiters spend an average of 6-7.4 seconds skimming through submitted resumes for details. The study suggests that the time spent may have reduced due to the unprecedented amount of unemployment. Recruiters seemed to be overwhelmed with applications for every position. The eye-tracking study also revealed that recruiters spend most of their time scanning the top, left, and bottom of the resumes. Amongst the top areas where recruiters spend their time is:

  • Name
  • Current job title and company
  • Previous job title and company
  • Current and previous positions with their dates
  • Educational background.

It was also noted that visuals like a photograph are distracting and should not be added. Additionally, some recruiters may become unconsciously bias when you add information like age, sex, and address. For example, if I reside in Africa but I wish to apply for a remote job in the United States, adding my address may be a point of bias so it will be better to exclude that.

Remember Glen who we talked about at the beginning? He’s got just one year of experience working in real-estate data analysis projects. To get the job, he has to leverage his experience. He could write more about projects he has done that the company may be interested in, the tools he used, and the GitHub link to the project. The projects section should be prominently placed close to the top of the resume and have attractive business-like titles not something like an academic thesis.

At this time, you may have enough information from the inside-the-company sources or the skills, tasks/ responsibility section of the vacancy placements.


Congratulations! You’re now ready to land your first data job. Do ensure to review your resume again and again before applying for each job. You may have to create different variations of the resume depending on the vacancy you find or come to know of.