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Top Skills Required to Be a Data Scientist

Updated: 5 December 2024, 8:15 pm IST

The field of data science education is changing rapidly in India. Professions like data scientists, big data engineers, and business analysts are gaining popularity among the most in-demand jobs in the country. As per a recent Data Science Education Report, the global data science education sector is likely to reach $378.7 billion by 2030. Similarly, the Indian industry of data science education is also experiencing a skyrocketing jump to reach US$ 1.391 billion by 2028 from US$ 204.23 million in 2023.

The surge in growth, propelled by India’s data-driven industries, has made data science a bankable career for Indian students. In this post, we are discussing the top skills needed to be a data scientist that helps youth excel in this field.

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Scope in the Data Science

What is Data Science? Scope in the Data Science Industry

Data science is a process of separating and streamlining volumes of raw data to present insights from them. In the current scenario, not a single sector is untouched by data science. Be it manufacturing, pharmaceuticals, retail, aviation, education, gaming, and more, every sector and almost every individual is somehow or the other involved in the field of data science. Industries use data to achieve business goals by making informed decisions presented by the data.

Overall, data science helps companies in various ways to make better and more profitable business decisions. It interprets and analyses data to decipher crucial information, classify between organized and unorganized data, and analyze trends in the future.

All this makes data science highly in demand and an inescapable area of career choice for youth in India.

Since more and more students are getting inclined towards a career in data science, it is important to consider the skills needed to be a data scientist**.** Let’s take a look at them below.

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Key Skills for Data Scientist

Key Skills Required to Excel as a Data Scientist

Data scientists require many updated skills including technical and soft skills to achieve greater success in this field of career. Below are some such skills that data scientists should be proficient in.

Technical skills

· Programming Language and Database – One of the top technical skills for data scientists is proficiency in programming languages. This skill helps them to manipulate data and automate tasks. Python, R, and SQL are some key programming languages used for analyzing data and managing databases. With strong skills in programming, data scientists can efficiently handle large datasets to create custom solutions using data processing tools.

· Mathematics & Statistics – Maths and statistics are critical to analyze the accuracy of data and they help data scientists to make the right business decisions. To excel and go further in your data science career, you need to be familiar with the concepts of mathematics and statistics

· Data Wrangling – This skill involves cleaning data and transforming the raw data into more usable ones. With this skill, data scientists can prepare data for analysis, while ensuring the accuracy and quality of the data.

· Data Visualization – Data visualization is the graphical representation of data analysis to make it easy to comprehend. Data scientists use data visualization to transform complex data into useful insights using various tools. The process involves creating dashboards, bars, graphs, etc. to effectively communicate data in an easily understandable way.

· Machine Learning (ML) – Data scientists create predictive models using machine learning. With these skills data scientists can predict outcomes and help businesses with data-driven strategies.

· Deep Learning Skills – Deep learning is a step ahead of machine learning. Being a subfield of ML, deep learning emphasizes more on robust algorithms. These algorithms are termed artificial neural networks and they help track complex problems. With this skill, data scientists can develop advanced models that can provide pioneering solutions in various fields.

· Big Data – Big data analyses huge datasets that are beyond the capacity of traditional tools used for data processing. Skills in big data are critical as they help uncover insights and improve the workflow of data by assisting in making better decisions backed by data.

Soft Skills

· Problem-solving skills – Data scientists require good analytical and critical thinking to resolve challenging issues of data. Their ability to think creatively can help in generating new approaches to the scope of inferring and analyzing data.

· Communication skills – Besides maths and statistics, a data scientist should be proficient in communication and presentation skills too. This way, they can help people understand the analyzed results to make their work valuable. Data scientists need this skill to tell compelling data stories.

· Collaboration – Teamwork is an important aspect of every field including data science. Hence, data scientists are required to collaborate with team members from various departments and should be capable of presenting recommendations driven by data to support organizational goals.

Career Options in Data Science

Career Options in Data Science

A career in data science starts with your interest in mathematics and statistics. These are the subjects that are predominantly required in the study of data science. A data science degree requires time as you cannot be a data scientist overnight. Moreover, it requires skills and experience to go further in this career. Below are some of the various job opportunities that data science brings to you.

The various entry-level positions that a data science degree holder can start a career with are:

· Data Analyst

Salary: Rs 4 lakh - Rs 9 lakh per annum

· Business Analyst

Salary: Rs 3 lakh - Rs 16.9 lakh per annum

· Data Engineer

Salary: Rs 3.5 lakh - Rs 20.9 lakh per annum

In addition to the entry-level positions, below are some other roles that a data scientist can take up as a career:

· Business Intelligence Developer

Salary: Rs 3 lakh - Rs 16 lakh per annum

· Analytics Engineer

Salary: Rs. 2. 6 lakh - Rs 21.9 lakh per annum

· Data Specialist

Salary: Rs 2.1 lakh - Rs 23 lakh per annum

· Data Manager

Salary: Rs 1.2 lakh - Rs 26.8 lakh per annum

· Data Architect

Salary: Rs 14.4 lakh - Rs 50 lakh per annum

· Machine Learning Scientist

Salary: Rs 8 lakh - Rs 60 lakh per annum

· Statistician

Salary: Rs 2 lakh – Rs 17.2 Lakh per annum

Overall, the opportunities for jobs are astounding for experts in the field of data science with varying salary ranges depending on your experience, the location of the company, and other criteria. To grow in this field, it is good to be equipped with the skill sets and gain as much exposure as possible.

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Summing Up

Data Science is an evolving field and it requires students and professionals to be constantly updated with the recent trends. This is because the tools that you have mastered today may become obsolete tomorrow and might be replaced with advanced ones.

Hence, it is important to choose the right data science program or degree to get the best education in the field. Amity Online University offers several online data science degree courses:

· M.Sc. (Data Science)

· MBA with a specialization in Data Science

· BCA with a specialization in Data Analytics

· BBA with a specialization in Data Analytics

Depending on whether you are looking at a UG or a PG course, you can enroll to excel in the data science profession. A UG course is the most sought-after globally, however, a PG program gives an edge to students in defining their role better. The better skills you gain, the better your chances to get more rewarding job options. Visit Amity Online to learn more.

Siddharth

Author

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frequently asked questions


What are the top technical skills required to be a data scientist?

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Programming language and database skills, data manipulation and analysis skills, skills in mathematics and statistics, data visualisation skills, machine learning, big data, and model deployment are a few technical skills required to be a data scientist.


Why is programming important for a data scientist?

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Programming is an important tool that is used by data scientists to accumulate and examine data to solve business challenges.


How important is statistical knowledge for a data scientist?

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Statistics is crucial for data science as it provides the required techniques to gather meaningful insights from data.


Can you explain what data wrangling is and why it is important?

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Data wrangling, also known as data munging, is an important process in the workflow of data analytics. It is a process of cleaning and structuring raw data to make it enrich and transform it into a suitable format for easy analysis.


What soft skills are important for a data scientist?

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Curiosity, business acumen, communication, critical thinking, teamwork, collaboration, and storytelling are some soft skills required for a data scientist.


How can aspiring data scientists develop these skills?

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Aspiring data scientists can enroll in some of the best data science courses and programmes to learn and acquire skills.


Are there any certifications that can help validate a data scientist's skills?

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Yes. Several certifications and other courses are there to help validate a data scientist's skills such as MBA with a specialization in data science.