There is nothing worse in the data analyst hiring process than feeling unprepared. Being unprepared in general is a terrible feeling, but when you’re applying to roles, it’s critical to do your best. How your resume will get screened, what you should ask about, your technical skills, and team interviews are very important. This article covers each of these steps and provides details into exactly what you should expect along the way.
What’s not in this article? We’re not going to tell you exactly what your prospective employer actually wants from you. We can’t tell you the types of questions you’ll be grilled on around your technical skills. These things require a lot more detail than we can handle here.
For now, let’s keep things to the basics so you know what you’re in for.
Resume Screening
Before an interviewee even gets a chance to speak with someone in a company about their background or potential worth, it’s likely they’re going to have a basic pre-screening of their technical and industry qualifications.
With the Analytics education pipeline booming through a huge variety of undergraduate, accredited classroom, and online certificate programs, it has become very competitive to get your resume to stand out.
Before 2015, few new analyst candidates would have structured training on their education side of their resume. Most came from backgrounds in economics, engineering, and mathematics. Now that these programs exist, having a strong background in hard skills employers want is essential.
An entire article is needed on this subject, but make sure your resume aligns with keywords in a job description. If you have a job with Python as a requirement, making sure you not the types of projects and libraries in Python you’ve used such as Pandas will likely help you get through these filters.
Initial Screening Call
There are some basic expectations to understand about the company you’re interviewing for and what HR and the hiring manager is most likely screening for as they vet you on the first call. This is really where your soft-skills interacting with others will be first tested in the data analyst hiring process.
Some questions you can expect to hear will likely include:
- Why this company?
- Why this industry?
- What’s your salary expectation?
- When can you start?
- If you’re not in the area, when can you relocate?
- Do you have full US working rights or will require any workers visa support for this role?
Undocumented and informal parts of the screening to be about “team fit” and the ability clearly communicate within the organization.
Being a data nerd doesn’t mean you’ll get away with being just head down in the data all day long without talking to team members, technical teams, product, and potentially clients. If you’re awkward with the first person you talk to this can be a red flag. It’s sometimes good to practice interview with a friend or colleague once or twice before you start interviewing to make sure you are confident and clear in the way you communicate.
Regarding applicants with visas, US restrictions and legal fees have been heavily enforced in recent years and many companies are no longer willing to support visas. This is due to several reasons which include legal fee costs for the company and the increased challenges from the government for analyst positions specifically. Whether this is fair or legal or not is not up for discussion in this article. The most important thing applicants need to do as a result of this is to be as transparent as possible about the visa type they have. Be clear about this early on in your resume and phone screening to set expectations clearly.
Data Analyst Technical Screening
Technical screenings can happen on the same call with the screening team as the initial screening, but it is in many ways some of the most important information gleaned from the interview process. If the position you’re applying for has Python, SQL, or Tableau listed as required experience and you have stated you have this experience, expect to prove your skills.
CoderPad and other platforms are regularly used for these types of validations of your skills and you should ensure you’ve done many practice problems if this is your first analyst role and your some refresher exercises if it is your second or third role.
Most analysts underestimate how important this step can be in the interview process, but they will weed out unqualified or unprepared applicants quickly.
Tools such as CoderPad and others help test questions can be sent to the applicants in advance and completed online within a designated time frame in around 1 to 2 business days. Another approach that some prefer is to have another analyst on the team do it. shadow interview with the candidate ad they address questions in real-time. This usually allows the team to see how candidates address topics they may not know about or have forgotten or need to troubleshoot.
If they run into a Python error, they may go google it and go straight to an answer of StackExchange to resolve the problem. If candidates can’t make it that far, it’s possible this type of resource will need far more coaching.
Take-Home Data Exercise
Technical screening questions are always useful, but many want to see not simple rote technical skills. Data analysis can extend beyond crunching numbers and candidates need the ability to generate insights, commentary, and understanding of datasets. This is where the home assignments come into play.
Some examples of what take home assignments may look like:
- Access StackExchange’s public API and pull down the top 100 questions for Python Pandas by views and plot the data
- An analyst can be provided some poorly maintained web log data that needs. If an analyst skips this step, their insights won’t be useful.
- Review a short coding assignment from a peer and make corrections so the code runs properly and summarize the results
You can see why employers want to see what you’re capable of. Can’t figure out how to pull from an API? Unable to identify messy data? Missing out on identifying obvious issues in a colleague’s code? These issues will all be red flags if solving these types of problems are outlined in the job description. Employers will have an expectation for this in the role.
This isn’t all bad news though. There are times when Analysts can’t solve all problems before they start a job due to their training. For instance, some analysts are heavy SQL users and don’t perform as much data manipulation within Python and vice versa. The important thing is that you hand in some kind of result of your work from the take-home assignment.
If you cant figure out how to fully solve the problem, leave detailed notes on how you tried to solve the problem, what you knew and didn’t know, and where you left off when the time expired. Unlike in academics, some problems simply aren’t common knowledge and handing in something is better than nothing.
There are many ways a hiring manager may look at this situation and decide if you’re a good fit.
Analyst Team Interviews
By this part in the interview process, you’ve passed the hardest steps and are now going to be likely asked in detail about your background, some specific use cases in your prior work or schooling, and your general interested and the types of team and people you like to work with.
These interviews are generally the least structured as they often take place with individual contributors and not with the hiring manager themselves as it’s ideal to understand if you’ll be a team fit or not. This said, if you are an analyst in this part of the process, ask the hiring manager or HR rep what you can expect when talking to the team.
To give you a sense of how broad these team structures can work as. They can vary from:
- a quick presentation of your take-home analysis
- a team lunch
- being asked to talk through a current issue with an analysis or dataset an analyst is currently having
- running through your resume again because it’s possible the interviewers simply haven’t had time to read it
The important thing is to be yourself, know how to speak to each element of your resume and any other piece of your portfolio as well as have some of the basic interview questions at the ready to answer. i.e. what are your strengths and weaknesses, what do you think you can bring to the team, etc.
Final Hiring Discussion
You’ve set expectations with HR, you’ve been tested on your skills by analysts, code exercises, and likely a take home assignment. You met the team and there weren’t any issues and you’re on to the last discussion about your role.
This is usually when you’ll get an offer around the role and this can sometimes meet or fall under your expectations for the exercise you’re interested in there – this is your last chance to truly think things over.
If there are areas of benefits that you haven’t recieved complete details on, start digging into those and ask for all that documentation. You’ll wnat to know about – health insurance, retirement plans, insurance policies, tuition reimbursement programs, etc. These small things can really add up for potential candidates. If you’re going to a company without them you should probably ask why they aren’t available.
Ignoring compensation and whether it’s a good role for you, if you’ve recieved the offer, the next step is to accept or decline and dive into getting ramped up for the role if you accept it.
There are plenty of things that you’ll want to get your hands on so you can get up to speed as fast as possible including:
- copies of existing reporting or reoccurring analysis deliverables
- a list of common key performance indicators (KPI) that the company looks at
- ask for the holiday schedule and make your new manager aware of any upcoming vacations you have planned to confirm you can still get that time off
There are many other things you may want to follow up on, but make sure you’re getting to the most important points so your new manager doesn’t have to do much for you until you’re onboard.
Hiring Process Summary
Now, here you are, you’ve made it through the data analyst hiring process. You’re off to the races to your new job and are getting ready to start at your new company. Like anything else in life, use the interview experiences you’ve had to learn for the future. You may not be changing roles for several years, so keep some notes on where you can improve next time.
With that, good luck!