If you are thinking about a career in IT and are passionate about statistics, take into consideration the Data Scientist profession. It is not an easy profession, but the demand for specialists is very high, and employers, especially U.S. companies, are willing to offer really attractive pay for industry professionals. If you think that you are good at math and analytics, it can suit you.
It is a professional operating a large volume of data. He or she needs a solid mathematic background to perform comprehensive analyses and find solutions for complex tasks. Besides, for setting such tasks, they need curiosity and creativity. The expert in this field is partially a mathematician, partially a computer scientist, and partially a trend-spotter.
It is an IT field that implies working with Big Data, i.e., large volumes of unmanaged information. For instance, it could be weather data, statistics on search queries, databases of viruses, and much more. The keywords here are “large volumes” and “unmanaged." In order to operate this data, specialists use statistics and machine learning. An outcome of such work is the reasonable forecast called a “Predictive Model”. In simple words, it is an algorithm that finds the best solution to the set problem.
Earn a data science degree or take data science online courses.
Learn data science fundamentals.
Learn relevant programming languages for data science.
Analyze free data sets to develop your practical data skills.
Develop visualizations and practice presenting them.
Develop a portfolio to showcase your data science skills.
Prepare for data science interviews.
Apply to relevant data scientist jobs.
To be a professional, you need practical knowledge of statistical analysis, expertise in building mathematical models (from neural networks to clustering, from factorial to correlation analysis), working with large data volumes, and a unique ability to find patterns. In practice, this demands the following skills and knowledge:
Besides, you should be proficient in:
Naturally, besides these skills, to be an expert, you should have a mathematic mindset, creativity, and passion for finding non-trivial solutions to difficult, multilayered tasks.
Based on the name of these two positions, it may seem that they both are used for the same profession and the HR agencies simply interchange them. But it is not quite so. In this section, we are going to explain the differences. First, let’s define who Data Analyst is: It is an expert, who conducts a visual analysis and interpretation of the data, and then reports back to the client.
The primary skills required include:
Data Scientist is an interdisciplinary expert, who can implement the roles of several specialists, and on top of that has a special skill.
The main Data Scientist requirements are:
However, in some cases, a specialist may not possess all of the above-listed skills but still be deemed a good Data Scientist if, for instance, he or she masters other skills. For instance, they could have only the basic knowledge of the listed programming languages but, at the same time, have excellent expertise in the industry for which the analysis is made.
According to the Payscale platform, salaries by city
Average data scientist salary in Bangalore - ₹1,013,493 / year
Average data scientist salary in Mumbai - ₹854,158 / year
Average data scientist salary in Pune - ₹809,220 / year
Average data scientist salary in Hyderabad- ₹855,749 / year
Average data scientist salary in Chennai- ₹837,670 / year
Now let’s review Data Scientists' salaries working at IT companies in India:
As you can see, the best highest for Data Scientists in India are offered by International IT giants with headquarters in the USA. Naturally, any professional would love to work in a multinational company and receive pay that doubles the country average for this position. However, to successfully apply, you need to have sufficient qualifications and at least 5 years of practical work because the competition is quite high. Thus, it is reasonable to start your career path in a smaller company and then take your chances with a global corporation after you acquire several years of experience, broaden your knowledge, and work on additional competitive skills.
To engage in Data Science, you would normally want to obtain a bachelor's degree in math, computer science, statistics, or economics. Considering that the specialists in this field have a lot of technical responsibilities such as the use of statistic formulas and sheets, ML, etc., you have to acquire the skills in all of these fields. But you don’t necessarily need to obtain certifications for all of them, most of the skills can be obtained on your own if you are passionate about math, and coding and are willing to acquire new knowledge. Different classes, online education, or even learning using YouTube tutorials can be sufficient. However, if you plan to work in a specific industry, for instance, the oil extraction industry, automotive industry, or any other, you should consider deepening your knowledge in this field.