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10 Most In-demand Skills of Data Scientist to Flourish in Your Career


If you plan to have a career in Data Science, then you also need to be aware of the required skills of data scientist and prominent Data Science Training Certification . 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.

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 and other skills of data scientist 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 on the skills of data scientist 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.

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.

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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 one of the major skills of data scientist. It 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.

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.

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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. There are numerous reasons why Apache is one of the top skills for data science.

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.

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. And, this is how data visualization is considered as one of the must-have skills for data science. 

Unstructured Data

Another major skills of data scientist include 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.

Hopefully, you are clear on the data scientist required skills in technical side, in the next section we will check through the soft skills needed for data scientist.

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 one of the important skills of data scientist to be able 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 one of the must-have skills of data scientist to be able to translate the data so that it can be understood by everyone within the organization either a technical or non-technical person.

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. Apart from the required technical skills of data scientists, JanBask Training also helps you to enhance your soft skills like team to succeed in your career. 

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 and the skills for data science.  

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How to Improve Your Fundamental Data Science Skills

Knowing what you need to get better at and doing how to get better at it are two different things, and improving the top skills of data scientist takes time. However, you can advance your profession in a number of ways by developing good habits, networking, and community involvement.

Make use of the resources available online

Online resources offer in-depth information on a wide range of data science topics, including both specialized and general topics. Simply by consuming internet content, you can advance your programming expertise, mathematical background, and the skills of data scientist.

  • Blogs: It can be a little challenging to get started with data science because there are so many blogs and resources available. But once you've identified the best data science blogs for you, they'll turn into a weekly resource that will, with little to no work, keep you abreast of the most recent trends and the skills for a data scientist.
  • Online Programs: You can now locate a university professor or a Google expert to teach you just about any data science skill you can think of thanks to the explosion in popularity of online courses over the past ten years.
  • YouTube videos: For visual learners and those who dislike traditional textbooks, YouTube is a veritable mine of educational material to master in the skills of data scientist.
  • Podcasts: Data science podcasts span a wide range of topics, from machine learning trends and industry insights to a show like the Data Engineering Podcast's more technical approach.
  • eBooks: Books about data science are frequently written by professionals and subject-matter experts in the field. Additionally, if an eBook isn't your thing, think about an audiobook to get expertise in the top skills of data scientist.

Getting better through practice: Practice makes perfect, no matter where you are in your profession. If you're employed, you can practice by putting in extra effort at work.

Join the Data Science Community and Participate: One of the most effective and rewarding study methods is collaborative learning, and networking with others in the field can help you get the required skills for a data scientist and grow your career in a variety of ways. Think of joining a data science community to enhance your knowledge further. 

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 with data science course certification. By learning this most in-demand and promising skill from a professional institute like JanBask Training you can also shape your career and earn a high salary.

Frequently Asked Questions

Q1. What is a data science dream job?

The Data Science Dream Job provides a self-paced online training course help aspire data scientists to learn the major skills of data scientist to land a fulfilling job. To get understand on this course, check out the data science dream job review online. 

Q2. Is training to be a data scientist difficult?

In comparison to other technical professions, data science careers have higher technical prerequisites. The learning curve for mastering such a wide variety of languages and apps is severe. But if one is determined and willing to work hard, nothing is difficult and you can master all required skills for data science.

Q3. Which degree suits a data scientist the best?

You'll need at least a bachelor's degree in data science or a computer-related field to start out as an entry-level data scientist, but the majority of these positions will call for a master's degree.

Q4. How much time does the data science course take?

Three to four years of undergraduate data science coursework in engineering and sciences are required for a bachelor's degree in data science.

Q5. What qualifies as data science?

The prerequisite for a bachelor's degree in data science is a class 12 grade with a 50 per cent overall average and proficiency in probability, calculus, and algebra-based statistics including all the skills for a data scientist. 

Q6. Is coding is one of the skills required for data scientist? 

The majority of highly compensated data scientists employ their programming talents despite the availability of no-code technologies. Although you don't need to know how to code to work in the data science field, you should think about learning it along the road to enhance your career.

Q7. To become a data scientist, which programming language should I learn first?

Researching the top programming languages for data science is a fantastic place to start because the optimal programming language for you will depend on the career you desire and the specialties you're interested in. The majority of individuals tend to choose Python since it has a vast array of beginner materials and courses.

Q8. Do I Need any Specialized Skills to Become a Data Scientist?

While machine learning and artificial intelligence are related to data science, you don't need to be an expert in either to become one. If these topics interest you, you can further your expertise in them, but if not, the fundamental information you learn  data science course will suffice.

Q9. Is it Possible to Work as a Data Scientist Without a Degree?

It is feasible to become a data scientist without a degree, despite the fact that many data scientist professions will specify pertinent degrees on their job criteria. As a substitute, you may enrol in a bootcamp, obtain credible qualifications, excel in the skills of data scientist and create a sizable data science portfolio to awe potential employers.

Q10. Can Someone Without Experience Become a Data Scientist?

You will need to demonstrate numerous types of experience in order to land your first entry-level data science position. Included in this are project-based experience gained through portfolios, educational experience gained through credentials and certifications, and community experience gained through collaborative and open-source initiatives.

Q11. Which skills of data scientist should I list on my resume?

The programming languages you are fluent in, libraries, software, tools you are familiar with, databases you have worked with, and projects you have completed are the most important skills of data scientist to list on your data science resume.

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!!

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