Data Scientist

What does a Data Scientist do?

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.

Who is Data Scientist?

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.

What is Data Science?

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.

How to become a data scientist in India?

• 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.

Data Scientist skills

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:

• Skills in visual data presentation.
• Practice in the implementation of machine learning (ML).
• Practice in the implementation of Deep Learning (DL), i.e., ML used to create complex abstractions.
• Practice in the implementation of Pattern Recognition, a technology that determines data patterns.
• Practice in data preparation, i.e., converting raw data to different formats to make it easier to use.
• Practice in text analytics, i.e., analyzing unmanaged data to generate key business ideas.

Besides, you should be proficient in:

• Statistics use and ML.
• Programming languages, primarily, SAS, R, or Python.
• Databases MySQL and Postgres.
• Software for visual data presentation and reporting.
• Hadoop and MapReduce.

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.

Data Analyst vs Data Scientist

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:

1. Expertise in the field of study, i.e., a certain area of business (for instance, the heavy machinery market).
2. Comprehension of the business peculiarities of the company that requires analysis.
3. Proficient presentation skills.
4. Knowledge and practice in visual data presentation (for instance, using Tableau), and the skill of making easy-to-catch attention and comprehensible for non-experts graphical charts.
5. Basic statistics understanding, skills, and practice in the use of the simplest data analysis software (for instance, Microsoft Excel).
6. Preferably but not obligatory, the ability to use one of the programming languages.

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:

1. Proficient presentation skills, a deep comprehension of the field of study, and the ability to provide reports in a comprehensible way to the non-experts.
2. Strong mathematical and statistical background, proficiency in data preparation, ML, text analytics, and Pattern Recognition.
3. Skills in operating Big Data.
4. Expertise in programming languages SAS, R, or Python.
5. An additional specialization, for instance, expertise in the heavy machinery industry technologies.

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.

Data Scientist salary in India

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:

• Microsoft offers Indian specialists a salary of about ₹1,180,000 or $16,000 a year.
• Google offers Indian specialists a salary of around ₹900,000 or $12,000 a year.
• Amazon offers Indian specialists a salary of around ₹1,464,852 or $20,000 a year.

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.

Top companies in India for data scientists

1. Flipkart
2. Walmart
3. Hewlett Packard Enterprise
4. IBM
5. Deloitte
6. Accenture
7. Amazon

Data Scientist qualifications

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.

Top data science colleges in India

1. IIT Delhi
2. IIT Roorkee
3. IIT Madras
4. IIM Calcutta
5. BITS Pilani (WILP)
6. Jain Online University
7. Manav Rachna Centre for Distance and Online Education
8. Chandigarh University Online
9. Amity University Online 
10. Online Manipal University Jaipur