It is estimated that nearly 150000 Data Science jobs will be created in India in 2020. Data Science has tremendous applications across industries, and it is emerging as one of the most popular career options.
What does it take to become a Data Scientist?
The first and most important thing needed to become a Data Scientist is education. It is essential to have a Bachelor’s degree. Approximately 85% of data scientists possess a Master’s Degree, while 45% of them possess a Ph.D. To become an expert in data science, check out our data science courses from the top institutions.
Another important aspect is the specialization or the course. For instance, 32% of data scientists have a background in mathematics and statistics, 19% in computer science, and 16% in engineering. A data science course from a recognized university or institution holds your resume higher.
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What are the required Technical Skills?
Education is a crucial requirement, but it is not the only requirement. You also need to have the right set of skills as well as a high technical aptitude.
- Statistical Modelling to understand and interpret the data sets strategically.
- Know at least one of the top programming languages like R, Hive, Python, SQL, and many more.
- Understanding of Statistics and Mathematics
- Understanding Software Engineering and Machine Learning to interpret and manage large data sets.
- Understanding Artificial Intelligence to help data science in getting solutions and results for specific problems.
- Data Visualization for graphical representation of data.
What are the Roles and Responsibilities of a Data Scientist?
You must pick an area of Data Science where you feel comfortable before finalizing or entering the field. Identify your proficiency and do your research.
- The work is to organize, store, and analyze data efficiently while viewing a company’s data system.
Top Data Science Skills to Learn to upskill
Research and Analysis
- It is the process of systematically applying logical and/or statistical techniques for evaluating data.
Refine business procedures
- The old data is substituted with new data for more efficient business management.
Smart decision making and planning
- Data is combined with analytics for improving decision making and planning for any business.
Generating actionable insights
- Actionable insights are obtained by analyzing the raw data sets.
Simplifying the complex procedures
- The complex datasets are analyzed to obtain useful data that is useful for the business.
Read our popular Data Science Articles
Benefits of becoming a Data Scientist
The plethora of job opportunities is just one of the many aspects of choosing this field. The high-in-demand job brings the following benefits:
- Data Scientist is the person responsible for uncovering the secrets that data keeps hidden. So, organizations put a high premium on the person who helps them understand trends and customer behavior.
- Leading Global organizations like Amazon, Google, Apple, etc. are searching for Data Scientists.
- Assured employment in the future with further enhancements of technology.
- Data Science has various applications in different industries, including Consulting, Manufacturing, Healthcare, Marketing, Pharmaceuticals, Manufacturing, and many more.
- According to a survey conducted in 2011, 94% of Data Science graduates have found it a satisfying job.
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What is the Average Salary of a Data Scientist?
Harvard Business Review calls the job of Data Scientist as the “Sexiest Job of the 21st Century”. If you have a look at the average salary of any data scientist, it averages about $1,20,000 per annum.
Know more: Data Scientist Salary in India
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What are the four components of a Data Science Project?
Before you are out there building your internal data science practice, it is really important to understand the structure of any typical data science project. If you miss out on any of the core components of data science, then there are high chances of failure of all the efforts you put in for bringing true value to the business.
The four main components of every data science project are:
1. Data Strategy – The development of data strategy is where you determine what data you are going to collect and why you are going to do it.
2. Data Engineering – This step is about what systems and technology you will utilize to access, use, and organize the available data.
3. Data Analysis and Mathematical Models – This is considered to be the heart of data science. Here, the data is analyzed with the help of different tools and mathematical models to extract valuable insights.
4. Visualization and Operationalization – After analyzing and modeling the available data, the data is visualized to make it easy for everyone to understand and take actions based on the conclusions drawn from the analysis.
What does a data scientist major in?
There are different ways to land a career in data science. If we categorize it, in general cases, there are three ways that people usually take it up.
1. Take up a bachelor’s degree in IT, math, computer science, physics, or any other related field.
2. Get a master’s degree in the data field or any other related field.
3. Directly gain experience in the data field by working in different sectors that you intend to work in.
Which degree is considered to be the best one for data scientists?
If you are willing to build a successful career as a data scientist, you should definitely look out to opt for Computer Science with a specialisation in Data Science. It is considered to be the most well-represented degree among data scientists, with 18.3% of professionals possessing it in the field.
This isn't really shocking because you need to possess good programming skills for building a successful career in this field. Other than that, 16.3% of data science professionals possess a degree in Statistics or Math, which is again not so surprising. It is a great option to consider if you are really good at math.