Interview Tips for "Data" Role

Over the last couple of years at least a hundred people have reached out to me via LinkedIn with questions related data and analytics interview preparation. There is definitely no formula to approach as it depends on various factors like role, job requirement, and the company. However, based on my interaction with folks, I would like to clear few myths and give important tips. I will focus these tips primarily for the roles involving - Data & Business Analytics/Business Intelligence/Data Engineering. Having said that, these tips would also be helpful for a wide range of other roles.

Based on my experience in the Business Analytics field over the last few years, I would suggest few traits which employers look from the candidate. I have been part of many interviews both as an interviewee and as an interviewer. Being on both sides of the table has helped me understand that requirements can vary from company to company and across teams. Therefore, I will list some common tips which should help candidate's preparation with more confidence.

• Inherit Behavioral Interview Mechanism: STAR (Situation, Task, Action, Result) is one of the most widely followed principle's in answering behavioral interview questions. Deploy the same mechanism while answering any technical questions, where applicable. For example: while explaining about any of your analytics projects, follow the STAR mechanism, instead of directly jumping into tools used and results obtained. Try to explain technical aspects as a "story". Remember that "storytelling" is also a key part of data driven and strategic thinking. While practicing (alone or with someone else), try explaining technical elements so that a non-technical person would be able to understand. Having real life relatable examples for technical concepts such as Principal Component Analysis (PCA), Gradient Descent, Random Forests, etc helps grab the interviewer's attention. This will also be beneficial to be on the same page as the interviewer, in case he/she does not know the respective technical jargon.

• SQL SQL SQL: I think there is no alternative to this. One has to be prepared to write SQL queries for "data" roles. Revising the window functions would be one of the best things to do a day before your interview. If you want to start SQL preparation in advance and need some help to push forward, I would recommend following "kudvenkat" youtube channel. I have explored many resources related to SQL and honestly this guy is one of the best in the business. This channel helps candidates with all levels of SQL proficiency.

• Know the Tool Version: This may sound trivial, but knowing the versions of tools one worked on is a good practice to follow. For example if you worked in the latest Tableau version then - 2020.2. Not knowing version does not impact negatively always. But knowing it implies that individual pays attention to details and creates a positive impression.

• Talk Data and Numbers!: Back your examples with data and numbers. Often candidates forget how important this could be. One simply cannot miss this key aspect of talking data when interviewing for a data related role! One has to be data driven in every aspect. Show your passion in every possible way.

• Deep Dive: It is very important to know all the details mentioned in your resume. It's a big let off when the candidate isn't confident with his/her own projects. This creates skepticism in the interviewers mind. When you quote numbers and data, it is also important to know how you arrive at those numbers. More often than not, employers would like to know further details. It necessarily may not be "grilling" for the sake of it but it is an aspect of "diving deep", which is a an important criteria to assess a candidate. Therefore, spend some time preparing about your projects/experience mentioned in the resume. This is very crucial particularly for new grads. Overconfidence does not help!

• Language Conundrum: Based on my interaction with various folks, I noticed that certain bias gets developed towards knowing a particular language - "R" and "Python" being the primary focus. Some employers definitely look for a mandatory skill, let's say, "Python". However, in majority of the cases to my knowledge, knowing any one of the languages would be sufficient. Since language can be picked up anytime and may change over time, employers look beyond just knowing the language. Approach and mindset to solve a problem would create a bigger impact than language to be used. This does not mean one should not learn new stuff. But better not to cram up a new language right before an interview. Learning happens with practice by default. Be honest in your interview. Do not commit to something which you don't know!

• Optimization: While doing "work" is one aspect. The "style" of doing is another - which is often impactful. This can be attributed to different areas. As an example, in coding using a "linter" could be an effective way to optimize the way one works. If you have used a linter, then make sure you bring that into the conversation. Wondering what is a linter? It is a tool that analyzes source code to flag programming errors, bugs, stylistic errors, and suspicious constructs. It can search for ways to optimize the code. In short, linter helps to write quality code - quickly, consistently, and efficiently. Example of a linter: PyLint. They are easy to use and integrate with most IDE's. Optimization in coding is just one example. Think of various ways where you have optimized the work.

• Being "Out-Of-The-Box": Time and situation permitting, show what you are capable of. If you have built cool interactive dashboards, played with real time data, or completed a Kaggle project, then make sure you highlight it. Who knows, you could be literally driving the conversation! This shows your passion, proactiveness, and being out of the box. Do not shy away from sharing such stuff. What additional things you bring on to the table is an important parameter.

Remember that interview is always a two-way process. The employers also look for candidates with equal passion. Be involved and definitely ask questions. Hopefully these tips would help you break some nerves. Happy Learning and Happy Interviewing!

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