Data science is one of the hottest new professions in the world today. As businesses search for innovative ways to target audiences, data plays a fundamental role in the process. Therefore, data scientists are potential assets that organizations are in dire need of. However, they won’t be hiring unless they find the right fit. Here are some of the questions employers go through while searching for the best candidate:

1. What is data science and how it is different from machine learning and artificial intelligence?

Many individuals and even professionals from the field confuse data science with data analytics or simple statistics. It is the science of making predictions and smart choices based on analyzed data. This is a basic question and an interviewer might start with this to test how much a candidate knows about their field.

2. State some current and future applications of data science

Data science makes use of machine learning and has found usage in every industry which produces goods for sale to consumers. In the future, it is going to play a role in enhancing artificial intelligence and leading innovation in almost every market.

3. Explain logistic regression

It is an outcome prediction model that uses certain variables to determine a binary outcome. For instance, logistic regression can tell whether a team will win or lose a match etc.

4. What are the confounding variables?

Confounding is a casual concept and a variable in this method impacts both the dependent and the independent variables in the situation.

5. What is the Law of Large Numbers?

It is a probability theorem which serves as the basis of frequency style thinking. It has applications in making future estimates based on the results of performing a similar experiment repeatedly. An interviewer might ask about this if it applies to their company or environment etc.

6. Elaborate a selection bias

Selection bias refers to the part of the sampling process which deals with the collection. Bias occurs when the subjects are not picked at random.

7. How do you know it is time to update an algorithm?

There are several instances where algorithms require an upgrade. A candidate must be well versed about these like when the data sources are evolving or a non-stationarity case comes up.

8. What do you know about cross-validation?

It is a method used to determine how the outcomes of statistical analysis can be generalized to an independent set of data. It is also known as rotation estimation.

9. What are some techniques for descriptive statistical analysis?

There are three main analytical techniques for descriptive statistics namely univariate, bivariate and multivariate. As the names indicate, there is one, two or more than two variables involved in each method.

10. Differentiate between Eigenvectors and Eigenvalues

Both these terms can be distinguished simply by saying that eigenvalues are the strength of transformation in the direction of eigenvectors. Obviously, if you are in an interview, it will take much more than a single line to convince the executive questioning you.