We get a lot of job search questions from folks trying to land jobs in analytics and business intelligence.

Here are answers to some of the ones that come up the most.

Hope you'll find this helpful!

Q: All of these supposedly entry level jobs come with lots of requirements. How can I get the experience if I’m not qualified to get my first job?

We get different flavors of this question all the time, because it can be so frustrating for job seekers. One common concern is that lots of entry level jobs will list 1-3 years experience required. So how can anyone enter the job market if they need to have experience first?

The short of it is, even though that job listing says '1-3 years experience', you don't really need that to land the role.

Taking this up to a higher level, the most important thing to understand about "requirements" in a job posting is that they aren't requirements at all. They are just a "wish list".

Companies know that the person who checks all of the boxes they are describing in their job post probably doesn't exist. If that person does exist, they wouldn't take an entry level job. They would be the department head. Almost without fail, job listings are unrealistic.

If a company bullets out eight different skills in their requirements section, there are probably actually only one or two that are really critical for the job.

You can usually figure out which skills are most important for any given role. Read the entire job description, including the responsibilities of the job. What kind of work are they describing? Are you going to own the SQL database, spend most days visualizing in Power BI, or slicing and dicing data from Google Analytics? If you can stack rank the skills that seem most important for the job, you'll have a good sense for which ones are really dealbreakers and which ones are nice to haves.

Q: What are the most important tools I should learn to be marketable to employers?

This all depends on exactly what type of role you're most interested in, but generally speaking, these are the ones I would focus on...

• Excel (it's everywhere, and more versatile than you think)

• SQL (same argument as Excel, plus with fewer people are really good at it)

• Power BI, or Tableau

• Python, or R

• Google Analytics or similar web analytics platform

The tools mentioned above are a great place to start if you're pursuing a career in business intelligence, as a data analyst. If you're looking for data science or data engineering roles, there will be some overlap, and also some additional tools and skills you should be diving into. We won't go deep into those now, but it's worth mentioning.

Regardless of which flavor of data person you are trying to become, there are some skills (in addition to the tools above) that we all need to develop...

• Communication

• Problem solving

• Strategic thinking

• Business acumen

If you want to be great in any data role, don't forget to build these skills to compliment the technical skills you're developing. They are just as important.

Q: I’ve heard people talk about project portfolios being really important. I don’t have one. What should I do?

Yes, project portfolios are really important, especially when you're just starting out.

Employers want to see your relevant experience. It's the easiest thing they can look at to make a quick judgment of whether you would do well in their open role (which is what they really care about).

Here are some of the benefits of having an up to date project portfolio...

• Passively market yourself so recruiters start coming to you

• Easily share relevant projects during the application process

• Provide concrete examples during the job interview

• Build your personal brand as a data professional

A project portfolio can take many forms. When it comes to the content you showcase, we recommend each project follow a similar format...

1. Lead with a high-level explanation of the business problem you solved (the goal is to make this digestible for anyone, and draw some people in)
   
   

2. Then, include some data visualizations to show off your storytelling skills
   
   

3. Finally, include a technical flex if you can. Give people who make it this far a chance to look under the hood. Show them your code. Share workbooks, calculations, etc.

The common mistake we see people making is jumping right into code files too quickly. Show off your communication skills and your ability to translate your technical abilities to business problems first, then go deeper and back it up with all the detail you want to show off.

There are lots of places you can keep your projects portfolio...

• your LinkedIn profile

• a website you build just for this

• Github

• Tableau Public or Power BI Publish to Web

• offline PDF files

There are pros and cons to each approach.

We recommend everyone at least keep their best projects as Featured posts, displayed at the top of their LinkedIn profile page. Any time you are in the job application process, recruiters will be looking here. Publishing projects here also allows for passive discovery of your work, which may lead to recruiters seeking you out.

We also recommend keeping your most relevant projects handy in individual PDF files, that you can easily share via email with potential employers.

If you have the time, energy, and money to build your own website to showcase your portfolio, you can do that too. But consider this a nice to have, and only do it if it's something you're personally excited about.

Q: What are employers actually looking for?

The short of it is, they are looking for someone who can do the role well, and who will be an enjoyable person to work with.

The latter part is really important. Don't come off as a jerk or you won't get very far. Be humble, excited, ready to pitch in to help the mission, and you'll check this box.

We'll spend more time talking about how they think of someone who can do the role well. It's tricky, because the only real way to know this is to get someone in the seat and see how they do. But employers cannot do that with every candidate so they have to take some shortcuts to try to assess how someone will do in short order.

Here are some of the things they'll do...

• Ask whether the candidate has held a similar position before

• Ask whether the candidate has completed projects similar to the work before

• Assess how experienced the candidate seems with the most critical tools to be used on the job (can be done in formal interviews, and by reviewing your background /projects online)

• Assess communication skills, business acumen, strategic thinking, and problem solving. These will typically come out in conversations about the role, past experiences, and sometimes specific case study exercises designed to understand abilities in certain areas.

Q: I’ve never done an Analytics interview before. If I make it to the interview stage, what should I prepare for?

Expect to meet with a number of people (usually 2-5) who will aim to assess you on the following dimensions...

• Cultural fit

• Technical skills (Excel, SQL, R, Tableau, python, etc - varies by role)

• Quantitative problem solving ability

• General business acumen

• Ability to self-learn

• Communication

• Enthusiasm for the opportunity

I won't go into detail right now on how they'll assess each one, but if you want to read more you can check out our Data Analyst Interview Guide.

If you just want the TLDR; expect to have some conversations on your background and project experience, be put through a technical assessment or two, and likely participate in a case study exercise to assess your problem solving abilities and quantitative thinking.

Hope these answers were helpful for you!