How to Prepare for Data Scientist Interview?

Have you ever wondered how a certain online app manages to offer you ‘suggestions’ on what to buy, what was your previous purchase and what are the upcoming discounts? Well, all thanks to Data Science. For a common man, Data science refers to acquiring and retrieving user data from a certain source for a particular purpose. So, if a ‘machine’ or a ‘software’ appears to ‘know you’ well, it is just data science working its magic.  

In today’s time and age, data science is the ‘it’ thing, where every purchase is a source of information about your choices and each and every customer is actually a product to be analyzed. Aspirants in the field undergo rigorous Data Science Training, in order to be able to develop skills that can be used in Data Science.

So, the basic function of a data scientist is to make useful information out of data collected. Data science training involves ‘fetching’ of information, analyzing the information and utilizing it for the growth and development of a certain business. While we as common customers, might assume that data science is used only for the ‘online apps’, then you are mistaken.

The data science training also involves an immaculate understanding of any form of ‘fraud’ that can take place. Here statistics and big data methods are utilized to ‘predict’ a possibility of a risk or a fraud.

Considering this fact, one can imagine the importance of being a ‘data scientist’ in the world today. Imarticus Learning is one such institute which has established itself in being a pioneer in quality data science training. For aspirants facing an interview, let us take a look at some of the most possible questions that can be asked.

1. How is Data science different from Artificial Intelligence?

Data science utilizes Machine learning in order to make future predictions. Artificial intelligence, on the other hand, involves Robotics and text analysis.

2. What do you understand by Logistic regression?

Also known as the Logit model, logistic regression is used for a linear combination of predictor variables in order to predict the binary outcome. 

3. What do you mean by Recommender systems?

This is also known as an information filtering system that is utilized to predict the preferences of a certain user towards a product. This subclass of information filtering is used in the areas of research articles, products, news, movies, and social tags.

4. What is ‘data cleaning’? How is it important?

Data cleaning as the name suggests is a process to clean data from various sources and use it to transform it into a format that is utilized as information by the data scientists. It is a tedious task and generally takes up most of the time. 

5. What do you mean by interpolation and Extrapolation?

Interpolation refers to estimating a value from two values that are known. Extrapolation means to approximate a certain value by using a ‘set’ of facts or values.

As one can see, there is a lot that goes into data science training and learning. Therefore, it is always a good idea to be prepared for an interview with proper knowledge about the field.