The Harvard Business Review named the data scientist the sexiest job of the 21st century. In this article, we’re going to discuss 3 Data Science Interview Tips that can set you apart from other candidates.
The data scientist is the highest paid role in the technology industry, with an average annual salary of $ 150,000.
Although their specific responsibilities may vary across industries and companies, most data scientists share a mission to help organizations create value from data. They do this by examining patterns and trends across many datasets, communicating results to a wide range of stakeholders, and creating and maintaining models for automated decision making. Becoming a data scientist, therefore, requires a unique, diverse set of skills that includes statistics, coding, business definition, and communication — all through a series of interviews and challenges.
In this article, we’ll share a few tips from the perspective of the applicant and the interviewer that will help you succeed in a data scientist interview and achieve your dream job.
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3 Data Science Interview Tips
1. Explore the job role carefully and get familiar with the company
As mentioned above, “data scientist” is an ambiguous term that can refer to any of the functions around data. Two data scientists from different companies or industries may find themselves involved in entirely different types of tasks.
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They spend most of their time in researching and visualizing data or creating the more details you will be. Therefore, it is essential to read the responsibility part of the job description or ask the interviewer: “What could a person look like in this role? If you know about this role, the easier It will determine for you whether this role is in line with your profile and interests.
Once you have chosen the proper role for you, the next step is to show the company your love for its business. This can be tricky for those starting out as data scientists or those who want to move into the industry because you don’t have much experience solving business problems in the sector you report.
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2. Data Science is all about storytelling
What can sometimes be underestimated is the task of obtaining data. Good data scientists are also effective narrators who can formulate their model outputs enough to convince stakeholders and thus drive real change.
Applicants applying for a job in the field of data are often expected to share their past experience with the project. It is a common cause to spend a lot of time defining technical efforts, such as cleaning data and correcting (hyper) parameters.
You’re reading the article, 3 Data Science Interview Tips – How to Set Yourself Apart
This can lead to your interviewers being overwhelmed with information they do not fully understand while reducing the time they have to discover your business and stakeholder management skills.
In addition, be sure to highlight the various roles involved (eg, product managers, data analysts, data engineers, QAs, and business operations managers), their responsibilities, and the way you communicate with them. If you hear this, your interviewers are likely to admire your sense of business and cooperation.
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3. Take home challenge matters – Shine & Rise with your technical skills
Hiring data scientists often involves a domestic challenge in which candidates receive one or more datasets and several business issues to resolve. Although submission requirements may vary, candidates are usually expected to share the code, model, and analysis.
Many candidates see this as an excellent opportunity to showcase their technical knowledge. R and Python are the significant languages of data science, and both have their packages necessary for data combat, statistical modelling and machine learning.
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