Interview Strategies To Land A Data Science Job
Appearing for an interview can be a daunting experience for many due to the uncertainty that surrounds an interview. It is always a concern for everyone to figure out the questions that might be asked, and some of them may not be even related to the job role at all. In a vast field like data science, the questions can be asked from any corner, which needs thorough preparations. These reasons are enough to put an interviewee in a dilemma, thereby decreasing the confidence of the applicant. In this article, we will guide you to crack an interview for the role of a data scientist with several tips that will create a real difference. Adequate Research To begin with, it is of utmost importance to understand the designation and job profile offered by an organisation. The job profile might specify skills, tools and techniques which should be clearly understood prior to applying. It is often witnessed that candidates apply for a particular position without understanding the job profile or having the relevant skills for the profile. If a job profile is not clearly mentioned, it is wiser to have a conversation with a human resource officer since data scientist positions vary from company to company. Furthermore, it is advisable to conduct thorough research about the organisation as well. The research will give the candidate a sound knowledge of the kind of work done by the organisation, on what scale it operates in the industry and the kinds of consumer it serves. In this way, the organisation’s demand from a candidate can also be evaluated prior to the interview. Creating A Digital Presence Creating a strong digital presence is the very first step; a candidate should take while applying for the job of a data scientist. A LinkedIn profile which looks professional to the core should be maintained that specify work history with details about projects worked on. Up next, a GitHub account is a must to give the recruiter a first-hand look at projects and codes which is more convincing than anything else. Another place to create a strong presence is Quora, where a candidate can answer several questions related to data science and help people in need. This way, a recruiter can witness the knowledge a candidate holds in regard to data science or how the candidate analyses the questions and answers them. Not to mention, StackOverflow is a good place to create an online presence since it is handcrafted for professional programmers to share questions and answers. Also, doing a wide range of projects on Kaggle will demonstrate your capabilities in data science techniques. A Fine Resume and Positive Personality The resume is the first piece of paper that helps to create an impression due to which the resume should be composed in a clear and crisp manner, with all the provided information accurate to the candidate’s knowledge. Moving on, preparing for the interview in the most crucial part as the preparation is the key to cracking the interview. A candidate should have a piece of thorough knowledge about the company and its operation as a hiring manager often tries to figure how interested the candidate is about the company. A smart hiring manager will put the candidate’s skill to test in order to understand how good the candidate is in terms of the skills mentioned in the resume. A candidate’s personality also plays a role in the selection and hence, it is good to keep a positive outlook and clear career goals. In this manner, the hiring manager will be able to understand whether the candidate is an ideal fit for the organisation or not, and what value the candidate brings to the organisation in the tale to reach his or her career goals. The candidate can showcase a number of projects such as Character Recognition and Forest Fire Prediction. To learn more about different kinds of data science projects and get a better idea, read our article ‘Top 10 Data Science Project Ideas for 2020.’ Good Knowledge of Data Science As the interview gets going, the interview panel might have a senior data scientist or software engineer along with the hiring manager to assess the candidate’s knowledge about data science. A candidate should prepare about a variety of topics such as machine learning, deep learning and conceptual questions about natural language processing. A lot of questions can be asked about programming along with problems solving questions related to the domain of the organisation. Most of the questions will be from statistics, so it would be an excellent initiative to brush up the basics of statistics. Moving on, the hiring manager might throw some behavioural questions to understand how the candidate reacts to different situations that often occur in the organisation. Last but not least, a number of culture fit questions might be on the way. The hiring manager might ask about the recent development in data science or about the latest tools in data science. The reading habit of a candidate can earn some brownie points since the manager would like to know their interest in the domain. Appearance and Hygiene The last point has nothing to do with skills or knowledge, but it is a critical point to be followed. Just like the resume, a candidate’s appearance is similar to a cherry on top. No organisation would like to welcome a candidate who is not well dressed or maintains good hygiene. For an interview, formals are the ultimate dress code one should carry. However, if a candidate is not sure, asking the recruiter about the dress code is a realistic option to follow. A candidate must be well-groomed and maintain proper hygiene, be it during the interview or while working with the organisation. Last but not least, one should be well prepared for the video interview too. Various companies are conducting interviews over video calls. Follow these tips to streamline your video interview process and increase the potential of landing a job.
Appearing for an interview can be a daunting experience for many due to the uncertainty that surrounds an interview. It is always a concern for everyone to figure out the questions that might be asked, and some of them may not be even related to the job role at all. In a vast field like […]
Cracking a data science job is requires a lot of effort. To help you, we have listed some strategies to land a data science job in 2020.
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["AI", "machine learning", "ML", "deep learning", "data science", "R", "Go", "Git", "GitHub", "GAN"]