How do I Prepare for a Data Science Interview? 20 Facts
How do I Prepare for a Data Science Interview? 20 Facts
If you have made it to the interview stage of your data science job hunt, then congratulations are in order for getting past the first two stages of the recruitment pipeline, which is discussed over at runrex.com. Now your focus shifts towards acing the interview so that you can walk away with a job offer. This article will look to help you with your interview through the following discussion.
How to prepare for a data science interview
Read the job description for the particular position you are interviewing for
Since data science roles are still relatively new, the responsibilities vary wildly across industries and companies. The gurus over at guttulus.com recommend that you look at the skills required and the responsibilities for the particular job you are applying for, and make sure that the majority of these are skills that you already have, or are willing to learn.
Review your resume before each stage of the interviewing process
Most interviews will start with questions about your background and how that qualifies you for the position. As discussed over at runrex.com, having these things at your fingertips will allow you to ease into the interview calmly as you won’t be fumbling for answers. Use this time to calm your nerves before the technical questions begin. You should also review your projects and be ready to talk about the Data Science process you used to design your project. Think about why you chose the tools that you used, the challenges that you faced along the way, and the things you learned.
Look at Glassdoor for past interview questions
If you are interviewing for a Data Scientist role at one of the bigger companies, then chances are that they have already interviewed other people before you, who may have shared these questions on Glassdoor. Read them, solve them, and get a feel of the questions you will likely be asked as outlined over at guttulus.com. If you can’t find previous questions for a particular company, solve the ones from other companies as they are usually similar, or at the very least, correlated.
Ask the recruiter about the structure of the interview
You should also ask the recruiter questions about how your interview will be structured, what resources you should use when preparing for your interview, what you should wear to the interview, as well as the names of your interviewers so that you can research them and learn more about them in preparation for facing them.
Conduct mock interviews
You should also ask for mock interviews from people who have been through the process before so you know what to expect. If you are unable to find someone to help you with this, solve questions on a whiteboard or notebook so that you can get the feel of writing algorithms someplace other than your code editor.
Practice the skills that you will be tested on
As is revealed over at runrex.com, when preparing for your data science interview, your preparation should be informed by the job description and the conversation with recruiters. Study the questions that you know will be on the interview. Look up questions for each area in books and online and make sure you review your statistics, machine learning algorithms, and programming skills.
The data science interview loop
The following are the stages you can expect to go through during the data science interview loop and tips to help you through each stage.
The Coding Challenge
Coding challenges can range from a simple question to more complicated problems like building a time series forecasting model using messy data. These challenges will be timed based on how complicated the questions are. They can be hosted on sites like HackerRank, CoderByte, or even internal company solutions.
The most important thing when doing coding challenges
As the gurus over at guttulus.com point out, when you are doing coding challenges, it is important to keep in mind that companies aren’t always looking for the “correct” solution, but that they may also be looking for code readability, good design, or even a specific optimal solution.
Preparation for a coding challenge
The following tips as covered over at runrex.com should help you with this:
Practice questions on Leetcode which has both SQL and traditional data structures/algorithm questions
Review Brilliant for math and statistics questions
SQL Zoo and Mode Analytics both offer various SQL exercises that you can solve in your browser
Tips for coding challenges
Consider the following tips:
Read through all the questions before you start coding to allow your unconscious mind to start working on problems in the background
Start with the hardest problem first, and when you hit a snag, move to the simpler problem before returning to the harder one
If you are done and have a few minutes to spare, read through your solutions one last time before submitting
It is okay to not finish a coding language as sometimes companies will create unreasonable tedious coding challenges with impossible-to-meet deadlines.
The HR Screen
HR screens will consist of behavioral questions, asking you to explain certain parts of your resume, why you wanted to apply to this company, and examples of when you may have had to deal with a particular situation in the workplace.
What to consider when it comes to the HR screen
You should keep in mind that the person you are speaking to here is unlikely to be technical, so they may not have a deep understanding of the role or the technical side of the organization. With that in mind, try to keep your questions focused on the company, the person’s experience there, and logistical questions, and make sure your answers don’t have any technical jargon.
Preparation for the HR screen
According to guttulus.com, the following tips should come in handy
Read the role and company description
Look up who your interviewer is going to be and try to find areas of rapport
Read over your resume beforehand
Tips for the HR screen
As explained over at runrex.com, the following tips are worth considering here
Come prepared with questions
Keep your resume in clear view
Find a quiet place to take the interview, and if that is not possible, reschedule it
Focus on building rapport in the first few minutes of the call
Don’t badmouth your current or former companies, boss, or colleagues.
The Technical Call
This is the stage of the interview process where you will have an opportunity to be interviewed by a technical member of the team. Such calls are usually conducted via platforms like Coderpad, which includes a code editor as well as a way to run your code. Occasionally, you may be asked to write code in a Google doc, which means that you should be comfortable coding without any syntax highlighting or code completion.
Preparation for the technical call
According to the gurus over at guttulus.com, the following tips should help you prepare
If the data science position you are interviewing for is part of the engineering organization, make sure to read Cracking The Coding Interview and Elements of Programming Interviews as you may have a software engineer conducting the technical screen.
Flashcards are usually the best way to review machine learning theory which may come up at this stage. You can either make your own or purchase one. The Machine Learning Cheatsheet is also a good resource to review.
Look at Glassdoor to get some insight into the type of questions that may come up
Research who is going to interview you as a machine learning Ph.D. will interview you differently than a data analyst.
Tips for the technical call
The following tips should help you ace this stage
It is okay to ask for help if you are stuck
Practice mock technical calls with a friend or use a platform like interviewing.io
Don’t be afraid to ask for a minute or two to think about a problem before you start solving it.
The Take Home Project
Take homes have been increasing in popularity within the data science interview loops as they tend to be more closely tied with what you will be doing once you start working. They can either occur after the first HR screen before a technical screen or serve as a deliverable for your onsite. Companies may test you on your ability to work with ambiguity (e.g. Here’s a dataset, find some insights, and pitch to business stakeholders) or focus on a more concrete deliverable (e.g. Here’s some data, build a classifier).
Preparation for the take-home project
Consider the following tips when preparing for a take-home project
Practice take-home challenges which you can purchase from datamasked
Brush up on libraries and tools that may help with your work such as Tableau for rapid data visualization or SpeedML.
Tips for the take-home project
As outlined over at runrex.com, the following tips should come in handy
Some companies deliberately provide a take-home requiring you to email them to get additional information, so don’t be afraid to get in touch
A good take-home can often offset any poor performance at an onsite as you will have demonstrated competency in solving problems that the company may encounter daily despite not knowing how to solve a particular interview problem. Therefore, if given the choice between doing more Leetcode problems or polishing your onsite presentation, it is worthwhile to focus on the latter
Make sure to save every onsite challenge you do as you never know when you may need to reuse a component in future challenges
It is okay to make assumptions as long as you state them.
The Onsite Interview
This will consist of a series of interviews throughout the day, including a lunch interview which is typically evaluating your ‘culture’ fit. It is worth remembering that any company that has gotten you to this stage wants to see you succeed as they have already spent a significant amount of time and money interviewing candidates to narrow it down to the onsite candidates.
Preparation for the onsite
The gurus over at guttulus.com recommend that you consider the following tips when preparing
Read as much as you can about the company
Do some mock interview with a friend who can give you feedback on any verbal and non-verbal tics you may exhibit or any holes in your answers
Have stories ready for common behavioral questions such as, “Tell me about yourself”, “Why this company?” among others
If you have any software engineers on your onsite day, there is a strong chance you will need to brush up on your data structures and algorithms
Tips of the onsite
As outlined over at runrex.com, the following tips should be of great help
Don’t be too serious and try to make it a pleasant experience for your interviewer
Make sure that you dress the part
Take advantage of bathroom and water breaks to recompose yourself
Ask questions that you are actually interested in
Send a short thank-you note to your recruiter and hiring manager after the onsite
The Offer and Negotiation
If all goes to plan, you will receive a job offer. Usually, companies will tell you that they plan to give you an offer over the phone. At this point, it may be tempting to commit and accept the offer on the spot. However, you should convey your excitement about the offer, then ask them to give you some time to discuss it with your significant other or friend.
Factors to consider when negotiating
When you are negotiating, there are several buttons you can press. The three main ones are your base salary, stock options, and signing/relocation bonus. Generally speaking, signing/relocation is the easiest to negotiate, followed by stock options, and then base salary. Therefore, if you are in a weak position, as for a higher signing/relocation bonus, but if you are in a strong position, increasing your base salary may be the best option as not only will it act as a higher multiplier when you get raises, but it will also affect company benefits like 401k matching and employee stock purchase plans.
Tips
Consider the following tips at this stage
If you aren’t good at speaking on the fly, it may be advantageous to let calls from recruiters go to voicemail so that you can compose yourself to call them back
Show genuine excitement for the company as you don’t want the recruiter to sense that you are only in it for the money
Always leave things off on a good note even if you don’t accept an offer from a company
Don’t reject other companies or stop interviewing until you have an actual offer in hand
Hopefully, this article will help you through the entire process of interviewing for a data science position, with more on this topic to be found over at runrex.com and guttulus.com.
