2021 Offer : Pay for 1 & Get 3 Months of Unlimited Class Access

- Data Science Blogs -

Data Scientist Skills Required For Your Dream Job In Organization


If you plan to have a career in Data Science, then you also need to be aware of the required data scientist skillset. In this blog post, we would discuss all the required data scientist skills that might help you in shaping your career as a data science professional.

So, let’s first discuss the job profile of a data scientist in an organization and then we would discuss the data scientist skills required and what are different data scientist skillsets .

Data Science Profile Introduction

Nowadays the demand for data scientists has increased considerably. A data scientist is responsible for predicting the growth and performance of an organization by analyzing and researching the organizational data.

Read: Introduction to Regression Analysis & Its Approaches

Have a look at the roles and responsibilities of the data scientists:

  • To collect data from multiple sources
  • Cleaning of high data volume
  • Data analysis and exploration to determine and predict trend and opportunities
  • To produce data-driven solutions and conquer challenges
  • To invent new algorithms
  • To make predictions through data visuals and reports

Data scientists use mathematics, statistics, and programming skills to organize a huge amount of data and provide business-related solutions to the problems that were hidden so far. They easily predict the analysis of the output of big data processing results . So, the skills of data scientists need to have strong mathematics and statistical skills. A potential data scientist may possess all these skills and have knowledge of data science tools and techniques. He may acquire online training and get certified for the same as well.

Required Qualification of Data Scientist

Data scientists are expected to possess some of the basic skills for data scientists are deep thinking, intellectual curiosity, ability to discover new concepts, etc. A data scientist’s motivational factor is not money instead is the ability to solve complex and typical data problems. They tend to discover the hidden truth behind to find the optimal solution.

Read: R Programming for Data Science Tutorial Guide for Beginner

As far as an academic qualification of a data scientist is concerned then they must possess a specific statistical, mathematical and technical degree to become the same. For this multidisciplinary job profile, even those candidates who have completed Ph.D. in statistics can be suitable ones. Today online training programs can bring you both practical and theoretical data scientist skills and knowledge in no time. Mainly used programming languages by the data science professionals are R, SQL, Java, Hadoop, and Python.

“ Enroll now for a free Data Science Training Demo class and accelerate your career path”

Data Science Training - Using R and Python

  • No cost for a Demo Class
  • Industry Expert as your Trainer
  • Available as per your schedule
  • Customer Support Available

Technical Skills Required for Data Scientist

Technical Skills Required for Data Scientist

R Programming

R is the most preferred language for data science professionals and is specially designed for the data science needs. All the analytical data scientist skills required  can be solved by using R. However, R has a steep learning curve but still is being used as a programming language by more than 43% of the data science professionals.

Python Coding

Python is one of the most used and common programming languages that is another important skill of  data scientist along with C/C++, Java, and Perl. Several programmers use Python due to its simplicity and compatibility like features.

Various data formats can be used as input for this language and SQL tables can also be imported into the code. The user can also create their own data sets through Python and find them on Google as well.

Read: What is Neural Network in Data Science?

Hadoop Platform

Although you may not surely require Hadoop, it is usually preferred in lots of cases. Experience of Pig and Hive can also be beneficial. Amazon S cloud experience may also be an added advantage for this profession. As per a LinkedIn, post-Apache Hadoop is considered as the second most important skill for data scienctist. 

Hadoop can be used for data filtration, data exploration, summarization, and data sampling. Being a data scientist, if you may have to deal with a huge amount of data that cannot be stored at a place, then you will have to send it to various locations and there you will have to use Hadoop. It can help you in quickly sending data to various locations and places.

Data Science Training - Using R and Python

  • Detailed Coverage
  • Best-in-class Content
  • Prepared by Industry leaders
  • Latest Technology Covered

Apache Spark

Apache Spark is yet another data scientist skill required which has become one of the most popular big data technologies across the globe and is a Hadoop like computation framework. The one and the only difference is Spark is considered as a faster framework then Hadoop. This is because in Hadoop the work is read and written on the disc, while in case of Spark it is cached in memory.

Read: Deep Learning Interview Questions and Answers

Apache Spark is specially designed for data science to run the complicated programs quickly. Data scientists can also handle unstructured data efficiently with the help of Apache Spark. The features and speed of the platform make Spark a suitable platform for data science professionals. So, if you want to boost your current skills of data scientist and want to add more data scientist qualification.I advise you to start learning Apache spark from today.

AI and Machine Learning

Machine learning includes a neural network, adversarial and reinforcement learning, etc. If you want to stand out from other successful and experienced data science professionals then you must be aware of all the popular machine learning techniques that are logistic regression, decision tree, supervised machine learning and many more. You can solve prediction based organizational problems and solve them quite easily and quickly.

Read: R Programming Language Interview Questions & Answers

Machine learning is another data scientist skills required.There are very few data scientists that are experts in machine learning skills like supervised and unsupervised learning, computer vision, survival analysis, and reinforcement learning. Familiarity with machine learning concepts can help the data scientists to work with large datasets.

Data Visualization

A vast amount of data is regularly produced by the organizations that need to be translated and formatted. Management professionals require and use graphical data more than raw data. Data visualization tools like Matplottlib, Tableau, ggplot, and d3.js must be clear to the professional's that can help them in converting the complex results to a comprehensive form. Here the fact is that many professionals do not understand technical terms, so it is quite good for them to show them visual representations and results.

Through visualized results, organizations can get data insights quickly and grasp the facts and create new business opportunities.

Read: Data Science vs Machine Learning - What you need to know?

Unstructured Data

Data scientists must know the techniques to handle structured and unstructured data. Unstructured data is that data that is not stored in tabular form. It may be like videos, blog posts, social media posts, customer reviews, audio files, and text files. As such data is not streamlined so it is quite essential to sort this data so that it can be processed. Unstructured data analysis is also termed ‘dark analytics as it is complex to process and understand, but unstructured data can help in the decision-making process of the organization.

Read: Statistics Interview Questions and Answers

Non-Technical Skills Required for Data Scientist

Non-Technical Skills Required for Data Scientist

Communication Skills

Companies always look for those professionals who can fluently and clearly translate technical findings to any non-technical team like sales or marketing department. Being a data scientist, you may have to communicate with various departments of the organization like sales, marketing, operations, and others. So, you must have the skills to create story-line around the data so that anyone can easily understand it.


Data scientists cannot work alone, they need to work with executives, product managers, designers, marketers, clients, and developers. To collaborate with various team members, you must know how to deal with colleagues and teammates. It becomes easier to finalize your business goals with the help and support of your team members. You must have the skills to translate the data so that it can be understood by everyone within the organization either a technical or non-technical person.

Read: ARIMA like Time Series Models and Their Autocorrelation

So, when you are learning all the necessary skills for data scientists, you should put more efforts on effective teamwork. Define the right way to address problems to your co-workers. Teach yourself how to ask specific questions and provide feedback to improve communication skills for a data scientist job.

Good Intellect

Being Intellectual is an important and prominent part of a data scientist skill set. With high curiosity, they can acquire more knowledge. As data scientists spend most of their working hours with data, they can provide an accurate result. Moreover, they regularly update their knowledge and learn new technologies and tools to know the current trend of data science.  

Data Science Training - Using R and Python

  • Personalized Free Consultation
  • Access to Our Learning Management System
  • Access to Our Course Curriculum
  • Be a Part of Our Free Demo Class

“Register for a live training on Data Science with us and get your Data Science related basics right!”

Summarized View

Role of data scientists involves more technical skills than non-technical ones. In order to be a proficient data scientist, you need to learn and understand all the tools and technologies that may make the job easier. Companies deal with huge amounts of data that they may use for their business goals to increase their ROI, so they hire skilled and experienced data science professionals. By learning this most in-demand and promising skill you can also shape your career and earn a high salary.

I hope you enjoyed reading my article on data scientist skills. Your journey of becoming a successful data scientist is going to be pretty long. So, I wish you good luck and Happy Learning!!

Read: An Easy to Understand the Definition of the Confidence Interval

    Janbask Training

    A dynamic, highly professional, and a global online training course provider committed to propelling the next generation of technology learners with a whole new way of training experience.


  • S

    Satya Prakash

    This is great article, it is helpful .

  • M


    Good to become visiting your weblog again, it has been months for me. Nicely this article that i've been waited for so long. I will need this post to total my assignment in the college, and it has exact same topic together with your write-up. Thanks, good share. DATA SCIENCE COURSE MALAYSIA


Trending Courses


  • AWS & Fundamentals of Linux
  • Amazon Simple Storage Service
  • Elastic Compute Cloud
  • Databases Overview & Amazon Route 53

Upcoming Class

6 days 17 Apr 2021


  • Intro to DevOps
  • GIT and Maven
  • Jenkins & Ansible
  • Docker and Cloud Computing

Upcoming Class

6 days 17 Apr 2021

Data Science

  • Data Science Introduction
  • Hadoop and Spark Overview
  • Python & Intro to R Programming
  • Machine Learning

Upcoming Class

5 days 16 Apr 2021


  • Architecture, HDFS & MapReduce
  • Unix Shell & Apache Pig Installation
  • HIVE Installation & User-Defined Functions
  • SQOOP & Hbase Installation

Upcoming Class

5 days 16 Apr 2021


  • Salesforce Configuration Introduction
  • Security & Automation Process
  • Sales & Service Cloud
  • Apex Programming, SOQL & SOSL

Upcoming Class

12 days 23 Apr 2021


  • Introduction and Software Testing
  • Software Test Life Cycle
  • Automation Testing and API Testing
  • Selenium framework development using Testing

Upcoming Class

5 days 16 Apr 2021

Business Analyst

  • BA & Stakeholders Overview
  • BPMN, Requirement Elicitation
  • BA Tools & Design Documents
  • Enterprise Analysis, Agile & Scrum

Upcoming Class

6 days 17 Apr 2021

MS SQL Server

  • Introduction & Database Query
  • Programming, Indexes & System Functions
  • SSIS Package Development Procedures
  • SSRS Report Design

Upcoming Class

5 days 16 Apr 2021


  • Features of Python
  • Python Editors and IDEs
  • Data types and Variables
  • Python File Operation

Upcoming Class

12 days 23 Apr 2021

Artificial Intelligence

  • Components of AI
  • Categories of Machine Learning
  • Recurrent Neural Networks
  • Recurrent Neural Networks

Upcoming Class

19 days 30 Apr 2021

Machine Learning

  • Introduction to Machine Learning & Python
  • Machine Learning: Supervised Learning
  • Machine Learning: Unsupervised Learning

Upcoming Class

12 days 23 Apr 2021


  • Introduction to Tableau Desktop
  • Data Transformation Methods
  • Configuring tableau server
  • Integration with R & Hadoop

Upcoming Class

8 days 19 Apr 2021

Search Posts


Receive Latest Materials and Offers on Data Science Course