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Preparing for The Most Common Data Science Job Interview Questions

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The importance of data in the modern world is hard to overstate. Advancements in AI, machine learning, and platforms such as Google Analytics now mean that masses of data are compiled by businesses on a global scale each day. With big data becoming pivotal in the construction sector and other top industries using data to connect better with customers, information really is crucial to the global economy now.

All this means that working in a data science-related role is a smart move. Of course, such a demanding role means that you need the right qualifications in place first. Enrolling on data science masters programs, such as those offered by well-known Kettering University, is therefore a good option. At Kettering, the online data science degree contains all that you need to know to work with data and is convenient enough to fit around other commitments.

Know How to Prepare for the Right Questions in a Data Scientist Interview

There are a lot of things that you need to know when looking for a career in data science. You need to keep in mind that employers will be looking for certain things when they want to hire the right candidate.

Most of these discussions will come up in the interview. You will have to know how to answer the questions that they are most likely to ask.

Once you have gained a qualification like this, you can start to apply for jobs and be invited to interviews. Preparation is key to decent performance, and it is worthwhile getting a handle on the most common data science interview questions you might get asked. But what might they be?

‘Can you tell me about a recent project you have worked on?’

This is a very common question you could get asked when interviewing for a data science role. You need to know what answer the employer is looking for when hiring a data scientist.

Many careers in this field involve project-based work, after all. If you can, try to think back to a project that relates to using your data science skills. It is also key to remember to communicate clearly – but with the right level of technical knowledge – what you did and why you did things that way. If you are straight out of university or college, you can use a project you have worked on in your spare time or in your studies.

‘Tell me about an algorithm that you have created on a previous project’

Data science jobs are STEM-heavy and require candidates to possess advanced technical expertise in areas such as coding. You should be aware of the specific skills that data scientists are expected to have.

Although you need to explain your answer clearly, do not be afraid to get technical here, as this is what they will be looking for. Try to discuss the various models you used, the analysis you carried out, and how that fed into the algorithm chosen.


‘How did you solve a problem a recent project presented?’

Solving problems is a major part of a data science job and this means that you must be able to show competence in this area. Try to sum up concisely what the problem was, how you managed the project to address it, and what the outcome was. You should also include in your answer the reason why you chose a particular model or approach.

Preparation is key for data science roles

The importance of data science jobs means that they should be taken seriously. This certainly extends to the interview stage, which requires proper planning. If you can think about how to answer common questions such as those above, you will have a great head start.

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Source: https://www.smartdatacollective.com/preparing-for-common-data-science-job-interview-questions/

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