5 Tips for getting your first Analytics job

5 Tips for getting your first Analytics job

I know, hunting for your first Analytics job is not easy.

Recruiters don’t take you seriously, HR asks you why you don’t have 20 years of experience in the field at 25 years old, and no one calls you back.

That’s not how you were told things would go when you enrolled in your program: “you’ll get a job as soon as you graduate, and you’ll make $150K per year right away!”

5 Tips for getting your first Analytics job - easy money

The reality is setting in now, and you’re wondering why no one wants to give you a chance after studying for all these years.

To help you get out of this situation, I will share 5 tips to help you get your first Analytics job.

Think like a business owner

Let’s say for a moment that you own a store selling furniture. You’re looking to hire a salesman and you’re interviewing Mark for the position right now.

You: “Mark, why should I hire you?”

Mark: “I have spent many years learning about the different types of wood and fabric, so I know how to build and maintain furniture.”

You: “That’s great Mark, how will that knowledge be beneficial for my business?”

Mark: “I can give recommendation on how to maintain furniture to customers.”

Would you hire Mark? To be honest, he failed the interview. Can you guess why?

He didn’t explain to me how he was going to make money for the business. Do you think that this doesn’t apply for Analytics jobs?

Think again, a Data Analyst or Data Scientist is nothing else but a salesman. The difference is that instead of talking to customers, they are talking to data, extracting value from it and selling that value.

Next time you’re in a interview, explain clearly how you can use your skills to generate value, and ultimately money for the company.

Stop searching for the perfect solution

I’m really impressed by the technical skills of candidates, interns, and junior employees. They can run complex SQL queries, write complex Python and R scripts, and design new Tableau dashboards easily. Yet, they often have a lot of problems dealing with very big or incomplete data. They can turn a 1 hour report into a 1 week project because they keep chasing the perfect solution.

In business there’s often a time constraint where a 90% accurate solution that takes 50% less time to find is optimal. We’re not in school anymore where the most accurate solution means the highest grade. In business, the most money means the highest grade.

It’s always a trade-off in between the impact in dollars of the most accurate and the faster solution. For some companies like Amazon a tiny difference in accuracy means hundred of thousands, if not million of dollars. If you want to work for a company like Amazon then you can prioritize accuracy all day long. However, you have to realize that for most businesses there’s no material difference in between 90% and 100% accuracy.

Think about that, and next time you’re in an interview talk about how you manage the time-accuracy trade-off. Talk about how you’re not always chasing the perfect solution but trying to optimize the ROI of the company instead.

Use job postings to your advantage

Imagine if detailed job postings didn’t exist, and that the only information you had was the title, the company, and a short description.

Now think about all the information companies actually give you: complete description, list of skills, seniority level, responsibilities, etc.

You can easily compile a list of all the skills needed for you to get the type of job that you want.

The next time you apply to a job, think about what’s on your resume: Does it match all the requirements for the position?

To avoid tweaking your resume each time, try to come up with a resume that matches the average requirements for the job that you want.

Take advantage of transferable skills

An important portion of the Analytics work is communication with your clients (managers, directors, etc).

Instead of going all-in with your technical skills, differentiate yourself by talking about the communication skills you learned in previous non-Analytics jobs.

Learn to communicate clearly and efficiently, and to turn complex problems and solutions to simple sentences.

Another transferable skill is accountability. Show that you care about the accuracy and integrity of your work and its impact on the company.

Lastly, you can talk about your organizational skills. This is very important since you will most likely work on different projects at the same time.

Give examples of previous experience at non-analytics jobs where you had multiple things to do at the same time, and explain how you managed your workflow to be successful.

Play the numbers game

In most job markets today there are hundreds of applications for each open position.

The probability that you get a job is therefore very low, and to increase your chances you need to compensate by applying to more positions.

There are very few job postings for candidates with no experience, so dont be scared to apply to jobs that require 2 years or less of experience. 2 years or less of experience is still considered a junior position even if the word is not explicitly in the title.

Establish a routine where you apply to a specific number of jobs every week. Take a commitment on doing that until you get a job and it will pay off.

A word of caution: try not applying multiple time at the same company, it is often mot well seen and may make you look desperate.

Conclusion

Here are the 5 tips that we help you get your first Analytics job:

  1. Think like a business owner
  2. Stop searching for the perfect solution
  3. Use job postings to your advantage
  4. Take advantage of transferable skills
  5. Play the numbers game

These 5 tips made a difference for me when I was trying to find my first job in Analytics, and I hope it will make a difference for you too.

If you have other tips that can help others find their first Analytics job, leave them in a comment!

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