Analysts are people with high attention to details! This trait is visible across any endeavor they are involved in.
I once went to a Go-Karting event with a bunch of highly competitive analysts. A week after that evening, we had (apart from multiple discussions) an Excel (VBA based) simulation showing details on what happened on each and every turn, when someone overtook the other person, when did people take a pit stop, who couldn’t accelerate as much as they could and what not! We almost ended up creating personalized recommendations for each driver.
As an analyst, getting into details and studying them carefully, almost becomes your second nature. In an interview, you are likely being interviewed by someone who has been an analyst for a longer duration that you have been. Hence, you should expect a through and close examination of minute details.
This, and many more details are covered in our comprehensive ‘Ace Data Science Interviews‘ course. Make sure you check that out before you head for your next interview!
Many people new to the industry or who is trying to enter this industry are typically not aware and hence ignore these finer aspects. Hence, I thought I’ll create a list of these small things, which are typically overlooked by people coming for an interview. Please see that this is not a list of competencies which you are being judged upon (if you want them, you can read them here). You can almost treat this list as a checklist of things you need to avoid while you are being interviewed.
- You reach late for an interview.
- The folder containing your documents is all messed up. When someone asks you for the CV, it takes you more than 10 seconds to pull it out.
- During the case study round (which normally happens for analytics interviews), not writing your solution in a structured fashion. This is one point which so many people overlook. The idea is that whatever you write during the case-study should be re-usable at a later point. Typically, case studies evolve as you go through them. So you would need the same structure, multiple times during the same interview. You cannot be fiddling with papers when asked to re-calculate profits in the new scenario!
- If it is a coding assignment, not indenting and commenting your code. Same principle as the last point. It also shows, how much of your work would be re-usable by others.
- If you have done something wrong, defending it rather than accepting it and correcting it.
- Error / typo in a CV or a non-updated CV
- Not putting a structure / framework to your answers is a big red flag. An ideal analyst would always have his thoughts structured – starting from when he / she is telling about himself / herself to when they are solving a case study.
- Not stepping back to see the bigger picture. Quite often, being good with details can back fire. If there is a business problem / case you are solving, you should always take a step back and think about the bigger picture. Don’t get into the details unless you are clear about the business problem and its impact.
- Using calculators / excel too often – even when they are not needed. 33.33 times 6 is 200, you don’t need a calculator for this.
- Not taking shortcuts when they are available. If two factors compensate each other, you can directly knock them off.
- Not triangulating numbers or making sense out of numbers once they have been calculated. Do they tie back to the original problem?
Curiosity / Motivation:
- Not asking enough questions or good questions during the interview rounds or outside.
- Not asking for clarity in an ambiguous / amorphous situation
- Lack of energy at any point in time during the process.
- Discomfort in doing white board discussions during the interview.
- Not suggesting a few crazy (read out of the box) solutions during the case studies
- Suggesting too complex solutions to simple business problems
- Thinking about the problem on a single track (usually data driven solutions) rather than holistically (e.g. Marketing, Operations, etc.)
There were some of the behaviors to avoid in an analytics interview I know of. If you have more to add to this list, please feel free to add them through comments below. These are part of our comprehensive Ace Data Science Interviews course. That’s a guide you don’t want to be without for your next data science interview!