2022 Roundup: Data Science scope, top skills, careers and more

The data science sector is expanding and evolving rapidly. The importance of data and professionals with data skills is rising as technology, big data, and software advance. 

Data scientist positions are expected to rise by 36 percent between 2021 and 2031, according to the US Bureau of Labor Statistics, which is substantially faster than the overall average growth rate of 8 percent. This translates to an increase in employment opportunities of about 48,800 every year. 

Data scientist positions typically pay a basic salary of USD 1,00,910. Academic disciplines related to data science include statistics, mathematics, programming, and project development, and their value is rising as big data is increasingly needed by almost every business. 

At Online Manipal, students can enroll for an online M.Sc. in Data Science from the Manipal Academy of Higher Education (MAHE) or a PGCP in Data Science & Machine Learning from the Manipal Institute of Technology.  

We have published several insightful articles in our blog sections in 2022. Here are the selected 10 articles in data science.  

1. How can a mechanical engineer become a data science professional? 

Mechanical engineers are perfectly suited to a data science profile because they already have experience collecting and analyzing data for their work on product designs and projects. Factors such as use of computers and programming and mathematics are common between mechanical engineering and data science. Read more to know how a mechanical engineer can become a data science professional.

2. What is the data science lifecycle? 

A data science lifecycle is defined as the iterative set of data science steps required to deliver a project or analysis. The data science lifecycle involves five key phases- identifying problems & understanding business, data collection, data processing, data analysis, data modelling, and model deployment. Read to know more about data science lifecycle.

3. Career options after an MBA in Data Science 

Data science is a booming industry and among the most in-demand careers today. Pursuing an MBA in data science helps you explore high paying job roles like data science managers, product analysts, data architects, market research analyst and more. You will also get to work with top companies including Deloitte, Amazon, Accenture among others. You may be interested to know about the career options after an MBA in Data Science.

4. Top 10 data science companies in India 

Data scientists are in high demand across industries as every organization requires them to make better informed and valuable decisions. As a data scientist, you will get to explore lucrative career options in top companies like Accenture Analytics, Swiggy, GenPact, Tiger Analytics, IMB, Oracle and more. Here are the list of top 10 data science companies in India.

5. The data science roadmap explained 

Data scientists today are helping businesses effectively comprehend massive amounts of data from various sources and gain insightful information to make informed decisions. There are tons of information in the market regarding data science that is expanding rapidly, but with the right roadmap, you can ace their career. You can read about the data science roadmap.

6. Data science degree vs data science certification course 

A data science degree helps you explore more career options, internships and build a wider professional network. On the other hand, a certification program is low cost and allows greater flexibility than a degree. However, both open doors to high-paying jobs in this in-demand domain. You may like to understand the difference between data science degrees and data science certificate programs.

7. MBA Vs MSc in data science 

Pursuing an MBA in data science requires a combination of robust technical knowledge, practical abilities and managerial aspects. An MSc in data science helps aspiring candidates mark their career move in the industry with a data centric. Read to know the difference between an MBA and M.Sc. in Data Science.

8. Four pillars of data science 

Data science is a constantly evolving field, and it is important to keep up with the latest trends, tools and methods. However, you can’t ignore the four pillars of data science- domain knowledge, math and statistics skills, computer science, communication & visualization. Here are the details of four pillars of data science.  

9. Rising demand for data science in India 

Data science is a growing field, and the number of job openings is also on the rise. Factors like ease of upskilling, versatility and high paying jobs have further boosted the value of this industry. Read to know more about the rising demand for data science in India.

10. Data Science Vs Machine Learning: An overview 

Data science is an intriguing area in which unstructured data is cleaned, filtered, and analyzed, with the result being business breakthroughs. Machine Learning is a branch of data science in which tools and techniques are utilized to construct algorithms that allow machines to learn from data through experience. Learn more about the differences between data science and machine learning.