51 Latest Data Science Interview Questions
Tags: help, career, tutorial, datascience
Published: 2020-02-04 09:34:50

<p>Data Scientist, a job role that has been the center of attraction for a majority of millennials out there for quite some time now. Not only the people from the IT sector are fascinated by this career option, but it has gained the attention of professionals from other industries as well.</p>
<p><strong>And why not, Data Science is a field that is a boon for almost all the industries of the world and is a field that offers lucrative salaries to its professionals.</strong></p>

![Alt Text](https://dev-to-uploads.s3.amazonaws.com/i/cr6qyn24rcrndi1yeroa.jpg)

<p>But, being a Data Scientist is never a cakewalk. It's a tricky journey and you need to be skilled enough to land this dream job. <strong>And the trickiest part of this journey is its interviews.</strong> All those skills that you've acquired for becoming a Data Scientist will go in vain if you aren't able to crack these&nbsp;ticklish interviews.</p>
<p><a href="https://docs.google.com/spreadsheets/d/1eNBLcKqCVN9zZQvfGUmm5bAzsETqB_ugVOlUtmvJGYU/edit#gid=910850616"><em><strong>Your&nbsp;road map for becoming a Data Scientist</strong></em></a></p>
<p>So, here's a compilation of all those tricky questions that you might face in your next Data Scientist interview. All these latest questions are compiled by some top recruiters.</p>
<h3><strong>TOP DATA SCIENCE INTERVIEW QUESTIONS</strong></h3>

<p><b><em>Do Wait till the end!!</em></b></p>

<ol>
<li>
<p>What is Data Science? What are the differences between supervised and unsupervised learning?</p>
</li>
<li>
<p>Why do you want to become a Data Scientist?</p>
</li>
<li>Explain the difference between Data Science and Data Analytics.</li>
<li>
<p>Name the three types of biases that can occur during sampling.</p>
</li>
<li>
<p>&nbsp;What do you mean by the term&nbsp;Normal Distribution?</p>
</li>
<li>
<p>What is correlation and covariance in statistics?</p>
</li>
<li>
<p>How will you explain linear regression to a non-tech person?</p>
</li>



<li>
<p>Python or R &ndash; Which one would you prefer for text analytics?</p>
</li>
<li>
<p>What is dimensionality reduction and its benefits?</p>
</li>
<li>
<p>What is the goal of A/B Testing?</p>
</li>
<li>
<p>Explain Recommender Systems.</p>
</li>
<li>Which algorithm is used in Recommender Systems?</li>
<li>
<p>What is the p-value?</p>
</li>
<li>What is the significance of p-value?</li>
<li>
<p>How can you select k for k-means?</p>
</li>
<li>What is a confusion matrix?</li>
<li>
<p>What is Power Analysis?</p>
</li>
<li>
<p>Explain 'Naive' in a Naive Bayes algorithm.</p>
</li>
<li>
<p>Why Is Re-sampling Done?</p>
</li>
<li>
<p>What are the differences between over-fitting and under-fitting?</p>
</li>
<li>
<p>What is a Linear Regression?</p>
</li>
<li>
<p>What is <a href="https://data-flair.training/blogs/svm-support-vector-machine-tutorial/"><strong>SVM</strong></a>? Can you name some kernels used in SVM?</p>
</li>
<li>
<p>What is box cox transformation?</p>
</li>
<li>
<p>What is the difference between recall and precision?</p>
</li>
<li>
<p>What are the steps in making a decision tree?</p>
</li>
<li>
<p>Can you tell some clauses used in SQL?</p>
</li>
<li>
<p>What is a foreign key?</p>
</li>
<li>
<p>What is regularisation? Why is it useful?</p>
</li>
<li>
<p>What is root cause analysis?</p>
</li>
<li>
<p>What is Ensemble Learning?</p>
</li>
<li>
<p>How is <a href="https://data-flair.training/blogs/hadoop-tutorials-home/"><strong>Hadoop</strong></a> used in Data Science?</p>
</li>
<li>
<p>Explain cross-validation.</p>
</li>
<li>
<p>What Are Confounding Variables?</p>
</li>
<li>
<p>What is univariate, bivariate and multivariate analysis?</p>
</li>
<li>
<p>What is collaborative filtering?</p>
</li>
<li>
<p>Explain Star Schema.</p>
</li>
<li>
<p>When do you need to update the algorithm in Data science?</p>
</li>
<li>
<p>How is SQL different from NoSQL?</p>
</li>
<li>
<p>What are the drawbacks of the linear model?</p>
</li>
<li>
<p>What is Cluster Sampling?</p>
</li>
<li>
<p>Explain the benefits of using statistics by Data Scientists.</p>
</li>
<li>
<p>What is meant by &lsquo;curse of dimensionality&rsquo;? How can we solve it?</p>
</li>
<li>
<p>What are eigenvalue and eigenvector?</p>
</li>
<li>
<p>Can you explain the difference between a Validation Set and a Test Set?</p>
</li>
<li>
<p>Explain why Data Cleansing is essential and which method you use to maintain clean data.</p>
</li>
<li>
<p>Why don&rsquo;t gradient descent methods always converge to the same point?</p>
</li>
<li>
<p>How do you work towards a random forest?</p>
</li>
<li>
<p>Is it possible to capture the correlation between continuous and categorical variables?</p>
</li>
<li>
<p>What is pruning in Decision Tree?</p>
</li>
<li>
<p>What is skewed Distribution &amp; uniform distribution?</p>
</li>
<li>
<p>Explain the ROC curve.</p>
</li>
</ol>
<p>So this was the list of all the <strong>Topmost Data Science Interview Questions.</strong> Here are the answers to all these questions-</p>
<ul>
<li><a href="https://data-flair.training/blogs/data-science-interview-questions/"><em><strong>Answers to Top Data Science Interview Questions &nbsp;</strong></em></a></li>
</ul>
<p>&nbsp;Other than these questions, here is a collection of some other <strong>tricky technical questions</strong> that you might have to answer during your interview.</p>
<ul>
<li><em><strong><a href="https://data-flair.training/blogs/data-science-interview-questions-and-answers/">71 Tricky Data Science Interview Questions&nbsp;</a></strong></em>&nbsp;
<p>&nbsp;</p>
</li>
</ul>

![Alt Text](https://dev-to-uploads.s3.amazonaws.com/i/ihe1mjfoansgxryzxc5p.jpg)

<p><strong>All the Best!!</strong></p>
<p><em><strong>Thanks for your time.</strong></em></p>