Data Science is poised to transform fields ranging from healthcare to basketball! In the past few years, companies have been spending billions of dollars to hire the best data scientists, in order to capture the hidden value inside the immense amount of data being captured every day. Yet the terms “data science” and “data scientists” are not clearly defined. In 2017, Kaggle conducted an industry-wide survey to find answers to following questions:

  • Who’s working with data?
  • What do data scientists do at work?
  • How can new data scientists break into the field?

Data Scientist job role topped in Glassdoor survey of The 50 Best Jobs In America For 2017, and it is termed the sexiest job of the 21st Century by an article on HBR.  However, as per the survey, data scientists spend the most time doing the thing they enjoy doing the least i.e. finding, cleaning and organizing the data, with very little time left for doing the analysis.

To make your job easy, we are presenting here an industry guide on Data Science that provides career guidance discussing about various roles and responsibilities one can have in the field of Data Science. This career guide aims to discuss the following topics:

  • Is Data Science suitable for me?
  • Why Data Science can be a good career choice for you
  • Different job roles and responsibilities for Data Science professionals
  • Where can you find a Data Science job?
  • Top companies hiring Data Science professionals.

Is Data Science suitable for me?

This is one question which many professionals will have in their minds. They often think many times whether or not they can learn the required skills set to become a Data Science professional. But you should remember that every expert was once a beginner. If you’re a newcomer into this field, then you can read our blog to get a good introduction about Data Science. As per HBR article, knowing the ‘WHY behind their work is very important for a Data Scientist due to high failure rate of big data projects.

Overall, this Data Science guide covers three important topics:

  1. Overall demand and supply of professionals in Data Science
  2. A discussion about available job roles and responsibilities and information about  the skills sets  required to get into the job
  3. To help you know where you can find a Data Science job.

Why Data Science can be a good career choice for you

Advancement in technology has helped Data Science to show its impact and bring revolutionary changes across different industries such as healthcare, education, e-commerce, retail business, banking and finance, and manufacturing and so on. Realizing its strength, many organizations have started investing in Data Science to enhance their business.

Many more organizations, including both startups as well as MNCs, having seen the demand for Data Science service in the market, have started providing Data Science as Service (DSaaS). This factor led to the creation of many new jobs with various titles such as Data Scientist, Data Analyst, Data Engineer, Data Architect, etc. We will discuss each of these job roles in the later part of this blog.

Before that, let us look at some facts that suggest Data Science professionals are really in a lot of demand in the IT industry.

As per reports suggested by The Economic Times, the number of jobs opening in Data Science has increased by almost 76% on year-on-year basis. It says that nearly 90,000 job openings in this field are being advertised across different job portal websites currently.

Further, the report says that companies such as JP Morgan, Accenture, Microsoft, Adobe, Flipkart, AIG, Wipro, Deloitte, EY, and Vodafone are among the leading companies having  a greater number of job openings for Data Science professionals.

The Department of Industrial Policy and Promotion’s (DIPP’s) has helped startups by providing funds of Rs. 517.92 crores has paid dividends as 14% of job openings were recorded in tier-II cities. This shows the growth in the number of startups in Data Science.

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Even though Data Science has its impact across different industries,  the Banking and Financial sector lead the list of many sectors in hiring the most number of Data Science professionals. Around 41% of jobs created for Data Science professionals are from this sector alone. Many other sectors such as the energy & utility , healthcare , etc. also contribute to hiring these professionals.

As per Business Today, Ernst & Young (EY), one of the largest professional services firms in the world, is reportedly planning to hire nearly 14,000 employees for its Global Delivery Services (GDS) centers in India. Other companies from the same sectors such as Deloitte and KPMG have also announced that their plans to hire 40,000 and 8000-9000 professionals to strengthen their teams in India.

According to Srinivasa Rao, global vice-chair at EY GDS, there has been a large demand for digital transformation and innovation focused services from global clients which allowed auditing firms to expand their workforce.

Rao says, “We are no longer looking at the talent that is proficient in repetitive, standard, codified tasks as we have built more technology (using) automation (and) Artificial Intelligence into some of our basic delivery models”.

“Hence, we are looking and reaching for higher value talent. The areas we’re looking are typically at advanced analytics, cyber security, automation, and Machine Learning, and we are continuing attention around Artificial Intelligence.”         

These words tell us the growing importance of Data Science professionals, as well as the areas in which their expertise are being sought.

In addition to this, a report from Indeed, one of the top job portal website, shows that a 29% increase in the in demand for Data Science professionals year over year and a 344%  increase since 2013 – incredible! Isn’t it?

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Seen from one perspective, the demand for Data Science professionals is increasing continuously, while skilled employees in this field are growing at a slow rate of about just 14%, indicating a huge gap between demand and supply.

 A LinkedIn report of August 2018 says that in USA there is a shortage of about 151,717 people skilled with Data Science professionals.

According to Feyzi Bagirov, a Data Science advisor at San Francisco based B2B data insight vendor,the supply in supply-demand gap won’t close anytime soon”. He further adds that “Academia still struggles to propagate Data Science”.

Different job roles and responsibilities for Data Science professionals

As mentioned in the above paragraph, now we will focus our discussion towards different job roles and responsibilities available in this field. Following is the list of prominent job titles associated with Data Science:

  • Data Scientist
  • Data Analyst
  • Data Engineer
  • Data Architect.

We will discuss each of these job titles in detail in the below discussion. At first, we will see about the roles and responsibilities of a Data Scientist.

Who is a Data Scientist?

Data Scientists are the professionals who work with complex data available to them from different sources, applying various scientific methodologies and extracting some meaningful information from it. These professionals work with several elements related to mathematics, statistics, computer science and many more.

Data Scientists have to be very good at using Machine Learning technologies and applying various statistical methods to analyze the data that can be helpful to various organizations to make their business strategies.

Responsibilities of Data Scientist in the organization

  • Data Scientists need to work with the Data Science team, as well as cross functionally with other teams including back-end developers, product management to help define problems, collect data and use analytical models
  • They need to develop and use advanced software programs, algorithms, querying and automated processes to cleanse, integrate and evaluate datasets and models complex business problems
  • Data Scientists should know how to design efficient data mining and text mining frameworks with related tools
  • They should develop Machine Learning components and integrate these into business processes.

Data Scientist salary

How much does a Data Scientist earn?

As per the report provided by Glassdoor and PayScale,a Data Scientist in U.S.A., even with no experience can earn $100,000 annually. With little more experience, they can earn an annual salary up to $118,000.

Skill sets required to become a Data Scientist

Technical skills

  • Excellent programming skills in R or Python
  • Good knowledge of relational databases and SQL
  • Experience in MATLAB
  • Experience in Deep Learning frameworks such as TensorFlow
  • Experience with NLP algorithms and techniques is an advantage
  • Knowledge of Statistics and Math
  • Data Visualization and Reporting.

Non-technical skills

  • Intellectual curiosity
  • Business acumen
  • Analytical Problem-solving
  • Teamwork.

Soft skills

  • Require strong written and verbal communication skills
  • Need to have leadership skills
  • Should have the ability to inspire others and support other’s development to achieve full potential
  • Need to collaborate closely with engineering and BI teams.

Educational qualifications:

Data Scientists are highly educated. Most of them have a master’s degree and some of them have Ph.D.’s. A Bachelor’s degree in any of the fields such as Computer Science, Social Science, Physical Science, and Statistics.

The most common field of study are Mathematics and Statistics, followed by Computer Science and Engineering. A degree in any of these courses will give you the skills you required to process and analyze Big Data.

With this information, we hope that you got a good idea of all the important aspects that help you to become a Data Scientist. You can also find  online courses on Data Science that teach all the necessary fundamental concepts about Data Science and help you to become a Data Scientist professional.

Now we will discuss another important job title: Data Analyst.

Who is a Data Analyst?

Data analysts are the Data Science professionals that are responsible for gathering the data, structuring databases and creating and running models. They are also involved in preparing advanced types of analyses to explain the patterns in the data that have already emerged.

Organizations in nearly every sector such as healthcare providers, retail stores to fast food chains benefit from the work done by Data Analysts. The valuable information provided by Data Analysts to an organization can help them in a way to understand their customer needs and hence can provide a better service to them, helping them to enhance their business.

Responsibilities of Data Analysts in an organization:

Data Analyst salary:

How much do Data Analysts earn?

As per the reports of Glassdoor and PayScale:

A beginner in Data Analyst role may get a salary of up to $57,000 annually. As they gain experience of about 4-6 years, they can expect their pay to go up to $68,000 annually. However, salary for such professionals varies with organizations, the project they work in, and also with the experience and qualification they carry.

Skills sets required to become Data Analysts

Technical skills:

  • Data analysts should know any of these programming languages such as Python or R
  • Experience in SQL and also the working knowledge of relational database management systems (RDBMS)
  • Knowledge of Tableau with large data sets and distributed computing
  • Experience with extracting data from different sources and analyzing it properly.

Some of the tools used by Data Analysts are as follows:

  • Microsoft Excel
  • SQL
  • SAS software
  • Google analytics
  • Google AdWords.

Educational qualifications:

To become a Data analyst professional, a bachelor’s degree in IT, Computer science or Statistics can be advantage to you. Some professionals also pursue a master’s/Ph.D. degree in statistics/computer science which can also be helpful to you.

Some of the preferred areas of study to become Data analysts are Management Information Systems, Engineering, Accounting, Computer and Information Science, Mathematics and Finance, etc.

We hope that the information related to the Data analyst job title is helpful to you become a Data analyst professional.

Now let us see some valuable information regarding the Data Engineer profession.

Who is a Data Engineer?

Data Science is a broad field and requires professionals with multiple skill sets. These professionals are given different designations based upon the roles and responsibilities they undertake in an organization.

Like any other professional of Data Science, Data engineer professionals also hold key roles and responsibilities.

Data Engineers are the professionals who transform data into a useful format for analysis. These professionals work closely with Data Architects and Data Scientists. They often work with problems associated with database integration and unstructured data sets. They work with a goal to provide a clean, usable data which can be of great use to many organizations to enhance their business.

Responsibilities for Data Engineer in an organization

Data Engineer salary:

Reports from major job portal websites such as Glassdoor and PayScale reveal that an Data Engineer takes a good amount of salary.

In the U.S., the average annual salary for an entry-level Data engineer is about $103,000. Once their experience level  increases to about 4-6 years in this field, then they can get an annual salary up to $117,000, plus they are also eligible for an additional bonus of about $10,000.

However, the salary keeps changing across different companies and based upon projects in which they are working.

Skills required to become a Data Engineer

Technical skills:

  • Knowledge of any one of the programming languages such as Python, Objective-C, JavaScript, SQL, C++, Java, etc.
  • Knowledge of data modeling for both data warehousing and Big Data
  • Knowledge of Agile Methodologies and implementation
  • Experience in Google Cloud or Azure
  • Knowledge of Business Intelligence tools such as Business Objects, Informatica, SSRS, MicroStrategy, Tableau, and QlikView, etc. (Right tenses again)

Educational qualification:

Pursuing a degree in software engineering, computer science, information technology can be beneficial in getting a job as a Data Engineer.

Along with this, having skills in computer programming and software design, statistical modelling, python, SQL and Machine Learning, etc. can provide you an advantage in this field of technology.

We hope you now have enough information that helps you to become a successful Data Engineer (consistency with capitalization, sir!).

Now we will proceed further to look in detail about another important profession associated with the Data Science field i.e., Data Architect.

Who is a Data Architect?

Data Architects are the professionals responsible for designing, creating, deploying and managing an organization’s data architecture. These professionals work closely with the users, system designers and the developers on a project team.

Roles and responsibilities of Data Architect in an organization

  • Data architects need to develop database solutions to store and retrieve company information
  • They need to analyze the structural requirements for new software and applications
  • They need to apply systems engineering and systems architecture disciplines to data strategy implementation and operations
  • They need to work with the product owner and end-users to constantly deliver products in a highly collaborative and Agile environment.

Data Architect salary:

The data provided by Glassdoor and PayScale suggest that the average annual salary of junior Data architects is around $104,000, while like other professionals Data architects with experience also get more salary and it is up to $ 125,000 annually. They also get an additional bonus of $ 10,000.

As we with other professions, here also salary varies across different companies and it completely depends on the skillset and the experience level and qualification of professionals working in this field.

Skills required to become a successful Data Architect

  • Good knowledge of any of these programming languages such as Python, Java, Scala
  • Experience of working with relational databases such as Postgres, and MySQL, etc.
  • Experience of working on Cloud technologies such as AWS, Azure, OpenStack, and Docker, etc.
  • Knowledge of Agile Methodologies and ERP implementation
  • Knowledge of Data mining, Machine Learning technologies, and Data Visualization.

Education qualification

A bachelor’s degree in the information system, computer science, engineering or any related field can help you to become a Data architect professional.

Along with degrees, there are several other opportunities provided by companies such as IBM, Salesforce, and Hortonworks. Some certificate programs such as IBM certified Data Architect – Big Data, Salesforce Certified Data Architecture and Management Designer and Hortonworks Data Flow Certified NiFi Architect (HDFCNA) can help you enhance your skills and take you a step further in becoming a Data Architect professional.

Now we hope you got detailed information about prominent job titles associated with the Data Science field. Anyone with a strong desire to learn and excel in this field can become a Data Science professional. However, which of the job role you will be entitled to will completely depend upon your area of interest, your expertise on skillset, the experience level you have, etc.

Where you can find a Data Science job?

Having known these different job roles and responsibilities, now we will focus our discussion towards where any professional can search for a job in the Data Science field.

Finding a relevant job in any field is not an easy task to do. The same holds true for Data Science professionals as well when you start finding the relevant job that matches your skill sets and experience level. To help such professionals, certain job portal websites provide you with all the updated jobs in their job categories.

Some of the noted job portal websites such as Indeed, Glassdoor, and LinkedIn are very popular in recommending jobs. Along with these, there are several other platforms  too, that provide a number of job openings, wherein you can consider applying for a job to stand ahead of all the competitors.

Some of the noted platforms are as follows:

Hope these job portal websites can be helpful to you.

Top Companies hiring Data Science professionals

According to the Bureau of Labor Statistics, the job openings for computer and information research scientists – including Data Scientist is expected to grow by at least 19% by the year 2026. Another important factor to be noted here is that Data Scientist has been included on Glassdoor’s Best Jobs in America as well as Highest Paying Jobs in America reports, earning an average of $96,116 each year.

Here is the list of top companies hiring Data Science professionals:

1. Accenture

Company Rating: 3.8; # of Data Science roles: 54

2. Amazon

Company Rating: 3.8; # of Data Science roles: 338

3. Apple

Company Rating: 4.0; # of Data Science roles: 103

4. Facebook

Company Rating: 4.4; # of Data Science roles: 209

5. Fidelity Investments

Company Rating: 3.9; # of Data Science roles: 13

6. Google

Company Rating: 4.4; # Data Science roles: 89

# Data Science roles: 89

7. Intel

Company Rating: 3.9; # of Data Science roles: 29

8. Microsoft

Company Rating: 4.1; # of Data Science roles: 26

9. Twitter

Company Rating: 3.9; # of Data Science roles: 20

10. PayPal

Company Rating: 3.8; # of Data Science roles: 41


Today, Data Science has become one of the most discussed term in the IT industry. Data Science with its vast features has been responsible for creating more number of new jobs. The job titles such as Data Scientist, Data analyst, etc. are new and were not even heard by laymen a few years back, but with the kind of revolutionary changes Data Science has brought about in various industries, Data Science professionals have been much sought-after IT professionals.

To help such professionals easily find all the relevant job titles of Data Science under one umbrella, we have  presented this blog. This has been one of the series of blogs on Data Science. We will soon come here with more blogs, at which we will be discussing  more relevant information associated with this field.

Along with all the information above we would like to share a link of some of the wonderful online courses on Data Science that can be of great help to you.

If you think that this guide has been a success to find the relevant information, then we request you to share it in your circles, so that it can reach those who are also looking for the same kind of information as you.

Do let us know your thoughts in the comments section about what do you think about Data Science technology, its applications and future trends.

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