With an infinite amount of information waiting to be organized, filtered, processed, and served for a wide range of purposes, the requirement for efficient data scientists becomes the need of the hour. According to Harvard Business Review, a data scientist is one of the highest-paid personnel of the 21st century. Data science is certainly a diverse field that demands proficiency in both mathematics and computer science along with some domain-specific expertise.
Data Science: A Field To Flourish Your Career
For those who are aspiring to set foot into this profession and aiming to flourish careerwise, it is important to understand there are several strata of steps to be accomplished beforehand. Combating data science interview questions is one such crucial phase that a candidate needs to surpass with utmost confidence and strong knowledge backup in order to get hired. From the importance of R language in Data Science to multivariate analysis, there are plenty of areas that need to be covered while gearing up for the interview. Following are some important Data Science interview questions that are commonly asked in a recruitment drive conducted by leading organizations across the world.
How Data Science is different from Big Data?
Both the terms are closely related and dependant on one another. Though this particular question seems simple in normal circumstances, there are chances it can trick you during the intense interview phase. The answer to the question is quite straightforward. Big Data is a huge volume of data that can be structured, unstructured or semi-structured, whereas, Data Science is a domain that deals with slicing and dicing of the information collected by Big Data.
What is Recommender System?
One of the popular Data Science interview questions these days, Recommender System might also sprout during the interview. Recommender System is basically a collaborative and content-based filter that deploys a personality-based filtration of data. It is widely used in multiple fields such as movie recommendations, social tags, music preferences, etc. Recommendation System interprets a person’s past behaviour and provides them with relevant future suggestions.
Explain the Benefits of R Language.
R language is a prominent aspect of Data Science that assists in efficient data analysing. You must have learnt this language in your data science course online that focuses on building a software environment for data analysis. R is a programming language that includes a software suite used for statistical computing, a graphical representation of data, data manipulations, etc. Following are the primary benefits of the R language:-
- Helps operators perform calculations on matrix and array.
- Extensively support machine learning software and applications
- Offers a robust ecosystem for data analysis
In the era of digitalization dominated by Big Data and Machine Learning, it would come as no surprise that data scientist jobs are soaring high in demand. Landing a job as a data scientist requires more than just a strong educational background and mental prowess; it demands a proactive and confident candidate to tackle the complex interview process. Above are some of the important questions that interviewers might ask to evaluate your skills and expertise in the field.