How To Prepare For A Remote Data Science Interview
Even remote data science workers are not spared the dread of facing interviews for job opportunities. No matter how confident you may be of your technical expertise, the best of us walk in with butterflies in our stomach. However, most of this nervousness stems from the uncertainty around the entire interview process. Although all companies conduct their interview processes differently, most follow a similar template. By condensing these common patterns into a few actionable points, we have created a guide for you to ace your next data science interview. However, be assured that it will be a long, drawn-out process. Interviewing for data science roles remote or otherwise can take you through multiple stages over the course of a few months. Telephonic Interview Getting a referral and having experienced professionals advocate for you might get you to this stage, but you need to prepare well to get past it. A telephonic interview by either a technical recruiter or a data science manager is the first step for most companies hiring for data science positions. These calls will broadly assess if you have the right skills for the position you have applied for, and are generally short and to the point. It will also delve into your past project experience to ascertain if you are a good fit for the company. One way to handle your interview at this stage is to express your passion for the company you have applied for. Research well and tell the interviewer why it makes professional sense for you to take on this role and associate yourself with the company. Thoroughly review the job posting and compare it against your resume when talking to the interviewer. Furthermore, do not hesitate to ask questions that demonstrate you researched the company well. Written Assessment After you have cleared the telephonic interview, companies often send a home assessment. This will vary depending on the position you have applied for, but typically includes a dataset for you to analyse or even a coding assessment. Assignments also greatly differ depending on the company and will reflect what you will be doing on a regular basis if hired. The format also varies from company to company. While some may provide an online platform that is unmonitored, others may prefer that you log in with an interviewer watching you perform the assessment. Both will, however, be bound by a strict timeline. While the outcome of this assessment totally depends on the depth of your technical knowledge, it will be advisable to use detailed visuals to make it interpretable to business stakeholders. This tells the interviewer that you have a good understanding of how your work can drive business value. Interview With Data Science Manager This person will be leading the data science team, and maybe somebody you would be directly reporting to. Other members of the data science team/data engineers may also join in for the interview. While the first interview covered broad topics to assess whether or not you make a good fit for the company, this interview — done over Skype — will be quite technical. Expect them to comb through your resume to discuss the projects you have worked on in the past. Take time to explain the logic behind the methodologies you employed and the algorithms you used. Be prepared to meticulously go over everything you have mentioned in your resume — from the tools you used to the logic behind using those. They may also ask you to expound on some of your answers from the written assessment, so be sure to save your answers and revise them before you appear for this interview. Furthermore, think of ways in which you could have improved on the assessment. Although these tips should help you ace the interview, attempting to understand what the data science team is working on can help you greatly. Presentation Although these are quite rare, some companies may ask you to present the findings of your analysis — the one in the assessment, or from one of your past projects — using PowerPoint. You need not get flustered with colour coding or embellishing your presentation, although it should be visually appealing. The focus should be on your verbal communication with your audience (business stakeholders). What is the best way to handle this presentation? Explain in simple terms why you used the methods to arrive at your analysis, followed by explaining the outcomes in a non-technical language, and finally addressing the key takeaways. Final Interview This may usually be conducted by the HR department or even the CTO. They may ask about how you would like to grow in the company, or what you would like to learn on the job. This is an opportunity for you to reiterate your passion for the company and how you could bring value to the company. Since this is your final chance, do not hesitate to talk about yourself as long as it can tie back to your excitement for the job. Also, ask questions about the next steps and the future of the company.
Even remote data science workers are not spared the dread of facing interviews for job opportunities. No matter how confident you may be of your technical expertise, the best of us walk in with butterflies in our stomach.  However, most of this nervousness stems from the uncertainty around the entire interview process. Although all companies […]
Although all companies conduct their data science interview processes differently, most follow a similar template.
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Anu is a writer who stews in existential angst and actively seeks what’s broken. Lover of avant-garde films and BoJack Horseman fan theories, she has previously worked for Economic Times. Contact: anu.thomas@analyticsindiamag.com