This is part three of our four part series on how to land your first data analyst job. In this section we will examine the actual interview and what to expect. We will talk about what it is, key considerations of employers during this phase, and how to maximize your chances of getting an offer after your interview. If you would like to read about the other phases please see the links below.
Screening Phase
Viable Candidate Phase
Interview Phase – See Below
Negotiation Phase
What It Is:
Everyone knows what an interview is so we won’t spend time describing it here. Instead we’ll focus on how it typically works in corporate settings for analytics positions as the process may feel different for those who are recent graduates or coming from another industry.
The interview is when you’ll get to meet and talk to the entire interview team. In some places this may only be a person or two, but it is becoming increasingly common to have several panels of people participate in the interview. Generally it will be made up of the team you’ll be a part of in the future. You’ll likely talk to the hiring manager again (they’ll want more time to dig deeper with you), additional leaders in the organization (experienced interviewers to help with the evaluation), data analysts from the current team (there to asses your technical skills), and in some cases stakeholders from the business (to asses whether you are someone they can get along with day to day). Depending on how many people you meet you may be there for an hour or half a day. Regardless of length the overall goal is to dig deeper into your applicable skills and knowledge and likely do some behavioral (“tell me about a time…”) questions.
Key Considerations:
How are Your Critical Thinking Skills: This is perhaps the most non-negotiable skill for any data analyst. You need reasoning and critical thinking skills and must demonstrate them during the interview. A good way to do this is to talk about a problem you needed to solve in the past in which you came up with several possible solutions. Talk through the problem, the options you came up with, and the reasoning and logic you used to determine which solution to use. If the problem was technical in nature great, but if not don’t worry about it. Better to have a non-technical example that showed strong thinking than a weaker but technical example.
Can You do the Technical Work: Don’t think of this an a binary yes or no answer. Too many people who want to move into analytics think that they must go and get all of this technical training before even starting to look for jobs. Yes you need some tech skills, but chances are there is a lot of room for on the job learning. If you have the skills they are looking for then great, show them off and you have a great shot. If you don’t have the exact skills then focus on showing what you do have. Can’t code in SQL but know Excel really well? Use an Excel example and demonstrate your ability to learn. Also if for some reason you get some sort of coding quiz or test and struggle remember that they are looking at your syntax skills AND your thinking skills. Even if you can’t code through the problem you should still explain your thought process to demonstrate as much knowledge as possible.
Can You Translate Business to Analytical and Analytical to Business: Remember that the main objective of data & analytics is to use data to answer business questions. When you get a business question you’ll need to be able to translate that into technical actions, and when you get a analytical result you need to translate that into something a business stakeholder can understand and take action on. Find an example whether it be work, school, or personal where you wanted to answer something but needed to collect and/or analyze data in order to do so. The more creative the solution the better. The key is to demonstrate the ability to navigate both worlds and ultimately use data to help someone take an action. Don’t leave out the last part. Analytics without action is just academics.
Can You Handle Ambiguity: Many times in data analyst roles there will be problems that present significant amounts of ambiguity. It could be that you are creating a new process on the fly, it could be that the data is messy and you need to make decisions about how to appropriately clean it up, or it could even be that you are part of a team and you don’t know where your role stops and IT’s role starts. The key thing to demonstrate in the interview is that you can handle ambiguity and consistently take good (not perfect) actions. Every hiring manager wants someone who can solve problems and figure things out. The difficult parts of the job are often not the technical work but rather all of the little undefined things that require decision making. Show you are comfortable and capable here and you’ll be at a big advantage.
Can we Put You in Front of Stakeholders: Because the majority of analytics teams and departments are cost centers and not revenue centers, meaning they don’t bring in any revenue for the company, having stakeholder support is absolutely critical. Without it you are likely to be underfunded or possibly shut down. For that reason the manager needs to know that their data analysts can be trusted to work with business stakeholders and provide them the service and results that they need. You can think of this a little bit like a doctor’s bed side manner. If you don’t like or trust the doctor then no matter how effective their treatment is you’re still likely to rate the experience as negative. Same with business stakeholders, if they don’t trust you then they are much less likely to trust your results and use them to make better decisions. The key thing to demonstrate in the interview is any experience you have with customer service. Show that you can take care of customers or clients and you’ll be OK on this criteria.
How to Get Through:
Prepare 4-5 Examples Beforehand: Before you go to the interview (and probably before the viable candidate phase as well) you should prepare 4-5 of your best stories to use for when interviewers start to dig in with behavioral or technical example questions. I would suggest that you craft them so that you can tell each in about 3-4 minutes. Think about what you want the example to convey. Is it your communication skills, conflict resolution, analytical thinking, etc.? It is OK for an example to cover 2-3 of the bases but you should not use the same example over and over. If the person interviewing you is experienced then they will pick up on the things your example conveys even if they didn’t ask it. If they aren’t experienced they may ask their preset questions even if you have already touched on it. You can either reiterate what you already told them and expand on the example or go to a new one. Either way you should be prepared and rehearse your answers.
Tailor Your Communication: As mentioned above you will likely talk to a range of people as part of your interview. Assuming this is the case you need to pay close attention to who you are talking to and their role in the organization. If you are answering for a data analyst you may want to get a bit more in the weeds to show that you know your stuff. If you are talking to a VP you should stay away from the technical talk and focus on the big picture problems you have worked to solve. The key is to pay attention, know who people are, and do your best to tailor the level of your answers.
Be Consistent and Concise: It is likely that you will get some of the same questions across multiple panels of interviewers. If this happens be sure that you are consistent in how you answer. One of the silliest, but quite common, ways that people disqualify themselves is by giving the panel two different answers which comes out later when they debrief. Don’t tell people what you think they want to hear, tell the truth and be consistent. Also while doing so you should be as concise as you can. We aren’t talking about 1 sentence answers but you should not drone on for 5-10 minutes each time. If you sense the interviewers are cutting you off then you need to quickly pivot to shorten your answers for the rest of the interview. When in doubt err on the brief side and ask them to let you know if they want you to elaborate more.
Ask Questions: Throughout the process you should be consistently asking questions. First of all it helps you determine if you want the role. Second it helps to show your interest. But third, and most critical for the interview, it gives you context to help shape your answers. You should have a game plan going into the interview but as you learn more about the team, the way they work, and what they need you should be incorporating that into your responses. It can be hard sometimes to do this. In normal conversation it is probably easy, but in an interview you may be nervous and constantly thinking about what you are going to say next instead of listening. Fight that urge and pay attention the best that you can. It can take your answers from good to great if you can add in those little bits to help the interviewers see how your experience applies.
You can find a lot of guidance online for how to get through the interview. My advice is not meant to replace that but to supplement it with what is most applicable for data analyst roles. Please take advantage of our free tools and services to help you along the way. If you take full advantage you’ll at least have an advocate to help you navigate some of the difficult decisions.