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 the Recommender System?
One of the popular Data Science interview questions these days, Recommender Systems 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.
Data science is an amalgamation of data analytics, software engineering, data engineering, machine learning, analysis, business analytics and more. It includes Big Data which includes retrieval, collection, ingestion, and transformation of large amounts of data.
So what does a data scientist do? A data scientist is responsible for giving form to big data, analyzing patterns and advising decision-makers to bring in the changes that effectively add to business growth.
Required skills
To be a successful data scientist, knowledge of machine learning, understanding multiple analytical functions, hands-on experience in SQL database coding and a strong knowledge of Python, SAS, R, PIG, HIVE, Scala are a must. A data scientist would also be required to use a distributed computing framework like HADOOP and data storytelling.
Responsibilities of a data scientist
The responsibilities of a data scientist entail:
- Data cleansing and processing
- Identifying new business questions that can add value to the organization
- Developing new analytical methods and machine learning models
- Correlating disparate data sets
- Conducting causality experiments
- Data storytelling and visualization
Job Roles of a data scientist:
A data scientist takes raw data and turns it into meaningful information. The job role of a data scientist is multifarious:
- A data scientist identifies issues in the organization and uses data to propose solutions for effective decision making
- Algorithms are built by data scientists. They design experiments to merge, manage, and extract data to supply tailored reports to colleagues and customers
- Machine learning tools and statistical techniques are used to provide solutions to problems
- Data mining models are tested by them to select the most appropriate ones for use in a project
- They also assess the effectiveness of data sources and data-gathering techniques to improve data collection methods
- Researching which prototypes can be developed
In senior roles, a data scientist will also need to:
- Recruit, train and lead a team of data scientists
- Establish new systems and processes and look to improve the flow of data
- Evaluate new and emerging technologies
- Represent the company at external events and conferences
- Develop relationships with clients.
Data Science Courses 2022
A data science course comprises of several modules like Python R, Linear Algebra, Statistics, Machine Learning Algorithms, etc. The best data science courses are offered by IIT (Delhi), IIT (Kharagpur), IIM (Bangalore), IIT (Bangalore), etc. It is advisable to brush up basic mathematics as it would be a big help during the course.
For working professionals, online data science courses are advised. The best online courses are provided by SPJIMR, XLRI Jamshedpur, Harvard, MIT, and Microsoft. The Professional Program for Data Science includes technologies like T-SQL, Microsoft Excel, Power BI, Python, R, Azure Machine Learning, HDInsight, Spark.
Other options are courses offered by Amity University (Noida), Institute of Management Technology Online, Edwiser, Brainstation.
Data Science is the algorithm to success
With the spurt in the requirement for data scientists, it follows that it is one of the most popular domains in the job market. The next decade and probably more is going to be all about digitalization and data scientists will have a stellar role to play.
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