10 Industries Paying High for Data Science Specialist

  1. Introduction
  2. What Does Data Science entail?
  3. Industries Offering Lucrative Data Science Salaries in India
  4. Top Ten Industries in India Paying High Salaries to Data Science Professionals
    • Banking, Financial Services, Insurance (BFSI) Sector
    • Media & Entertainment
    • Healthcare
    • Retail
    • Telecommunications
    • Automotive
    • Digital Marketing
    • Professional Services
    • Cyber Security
    • Mining, Quarrying, and Oil & Gas Extraction Sector
    • Takeway       



The data science industry is dynamic. Year after year, new technologies are developed and deployed, and the change seems to be continuing into the next decade.

There is an increasing demand for data science experts worldwide. Employment chances would continue to grow through 2021 and beyond. Data is increasingly becoming a valuable resource for businesses in the digital era; hence, this tendency is logical. 

In this blog, we’ve compiled a list of India’s top 10 Industries paying the highest salaries for data science professionals.

The compensation package is not the only aspect to consider if you’re aiming for some of India’s best data science jobs. Job security, career advancement, and reputation are all factors that contribute to a job’s attractiveness.


What Does Data Science entail?

The practice of data science is the process of gathering, processing, archiving, and analysing data. It promotes data-driven decision-making, promoting an atmosphere of continual development.

The e-commerce site of Amazon, which is now the most popular online merchant globally, provides an excellent example of how data collection may enhance performance. Users’ home page visits are tailored to their searches, purchases, and expenditures on Amazon. In other words, it remembers data and gives prospective product suggestions that are appropriate for customer requirements.

The next great innovation and productivity frontier is big data. According to the MGI and McKinsey’s Business Technology Office’s study, a business may increase its operating margins by more than 60% by utilising data. 

Personal-location data can also assist consumers in paying less for purchases and services, resulting in a consumer surplus of around $600 billion. As a result, big data may be a game-changer when it comes to developing healthy economies.(Source)

Innovative applications may solve a wide range of serious problems, from enhancing diagnostic accuracy in medicine to revolutionising healthcare with wearable technology. Data science can also assist farmers and food producers in reducing food waste, increasing yields, and ultimately generating more money.

Many charitable organisations are now using data technology to create cutting-edge initiatives at the community level, as well as to enhance fundraising efforts through the use of predictive funding predictions. To date, there has been a lot of interest among governments in utilising data science to identify potential security risks and field monitoring activities.


Industries Offering Lucrative Data Science Salaries in India

Every business today demands data-driven decision-making. It implies that the primary responsibility of every data-driven organisation will be to do precisely that: gather, distribute, study, store, and act on data. By 2025, the value of the data science market is expected to hit $16 billion. (Source)

According to LinkedIn, there was a whopping 37% increase in data science employment over the previous three years. (Source)


Top Ten Industries in India Paying High Salaries to Data Science Professionals

  1. Banking, Financial Services, Insurance (BFSI) Sector

The BFSI sector has become one of the most innovative and leading adopters of data science in India. Every financial organisation is continuously looking for experts who can develop new insights from their data assets and improve overall productivity with better decision-making capabilities. 

According to research by KPMG in India, the Indian bank boards are already working on an average of four strategic projects using big data analytics to enable path-breaking business decisions. The research further states that most organisations believe that big data will be critical or essential to their industry within the next few years. 

The enormous growth in data to be processed and acted upon has resulted from an expanding number of use cases in the Banking, Financial Services, and Insurance (BFSI) industry. The sector has primarily focused on integrating data science throughout all decision-making procedures based on actionable insights derived from consumer data.

Data science and AI can help financial institutions to be more efficient in providing services to their clients, some of which include–

  • More accurate assessment of credit ratings
  • Faster collection methods 
  • Identification of new business opportunities 
  • Accurate prediction on regional preferences 
  • Detecting Fraud
  • Securing and managing customer data
  • Customer segmentation
  • Algorithmic trading


  1. Media & Entertainment

The prominent media and entertainment sector players, such as YouTube, Netflix, Hotstar, and others, have begun using data science to understand their consumers and provide them with the most relevant and individualised recommendations. Even ordinary entertainment channels are using user data and gossip news feeds.

According to a recent PwC study, India’s online television market will expand at a 21.8% annual rate from INR 4464 Cr in 2018 to INR 11976 Cr in 2023. From INR 3756 Cr in 2018, subscription video-on-demand services will rise at a 23.3% CAGR to INR 10708 Cr by 2023. (Source)

The adoption of this new persona of digital reality is focused on matching the users’ preferences and is evoked in the notion of addressability, as well as consumer interaction based on their choices. In this world where data influences everything, the media and entertainment sector is searching for data scientists who can collect, analyse, store, and offer recommendations while positively impacting the firm.

Data science strategies, especially artificial intelligence and machine learning, have scaled up the media and entertainment industry through– 

  • Personalisation 
  • Customised recommendations 
  • Targeted marketing 
  • Data security and protection 
  • Automated content generation for news, movies, music etc. 


  1. Healthcare

In the healthcare sector, where most data is unstructured, and it is difficult to gain access to and analyse all of the data, hospitals and medical centres need data scientists who can combine disparate heterogeneous facts. 

Data science has made it much easier to manage all of this information, from electronic medical records to clinical trials to genetic information to billings for wearable devices. Healthcare has become one of the significant producers of data scientist jobs in recent years.

In addition, data science has aided in the development and evaluation of health policy solutions that improve equity, access, opportunity, and quality of care.

Some of the areas with enormous scope to apply data science include –

  • Clinical trials
  • Pharmaceutical R&D
  • Patient monitoring and diagnostics 
  • Genomics
  • Health insurance 
  • Personalised medicine 
  • Organs, cells, tissue engineering

Building predictive models to discover diseases that go undetected in early stages. It helps doctors devise effective treatment plans for patients who have been diagnosed with a disease. By carefully analysing data from a large number of patient records, it is possible to predict the next course of action each patient’s illness will take. For instance, the information collected over time about a particular patient’s condition can help determine which medications they have a reaction or side effects to and therefore avoid prescribing them such medicines. 


  1. Retail

Even the worldwide epidemic, store closures, and layoffs couldn’t dampen data scientist demand for retail goods.

Consumers have grown accustomed to receiving every message they want in their inbox or on their phones in today’s world. The consumer-focused retail business thrives on personalisation and relevance, with one aim in mind: to understand the shopper’s behaviour and patterns through data.

Data science has aided in the improvement of customer understanding for retail organisations. Data scientists are highly prized in the retail industry because they combine a unique combination of solid data knowledge, business acumen, technological abilities, intuition, and statistical skills.


Data science in the Retail Sector helps to–

  • Understand the customer behaviour 
  • Increase sales, conversions, and revenues 
  • Leverage Big Data analytics to gain insight into consumer shopping patterns 
  • Identify specific groups of customers based on their location, demographics, preferences etc., that can be targeted with custom campaigns.  


  1. Telecommunications 

Now that people frequently utilise voice, text messages, social media, and other technologies to access telecommunications networks, telecom providers have access to massive data. Other data sources, such as website visits and past purchases, search patterns, and customer demographics like address and age, have been essential for telecom companies. The role of data science then enters as a result of this.

The development of valuable classifications and applications of this enormous data has been revolutionary for telecom firms, allowing them to serve their more diversified client base better.

Data science enables Telecom companies to–

  • Tap into new markets 
  • Increase customer experience and retention 
  • Improve machine learning capabilities within the network to create highly accurate models to deliver personalised content and services based on user behaviour. 


  1. Automotive 

Automotive manufacturers have benefited from data science because it revolutionised everything from research to design, production, and marketing processes. Autonomous driving is the use of computer systems for automobile control. Advanced analytics have driven the creation of automated vehicle systems that include sensors, cameras, and radar, as well as Global Navigation Satellite System, Inertial Navigation System (INS), Light Detection and Ranging (LiDAR), and more.

Data science’s role in the automotive industry is not limited to–

  • Advancing vehicle technology 
  • Designing vehicles 
  • Improving product quality and performance 
  • Providing emergency services if there is an accident

With automobiles growing more sophisticated and capable of gathering more information, it was impossible to measure wear and tear or track mileage, fuel efficiency, and routes without data science. Thanks to the force of data, prepare for the arrival of future vehicles that will communicate, collaborate, and operate without human assistance!

Every sector is attempting to take advantage of the power of data to succeed in the market. Consider enrolling in a data science course if you wish to join the data science movement.


  1. Digital Marketing

Businesses are now fetching enormous quantities of data from their consumers, including search results, social networks, display network traffic, videos, websites, CRMs, databases, and more. 

The usage of data science methods to analyse large volumes of data is critical because it aids in creating and managing business intelligence. Data science is increasingly being used for analytical purposes in digital marketing. 


This data-driven knowledge might assist marketing and brand managers in obtaining critical information such as –

  • What is the best time to set up an advertisement campaign? 
  • How much spend should be allocated for consumer acquisition at a specific time? 
  • Which social media platform or website yields maximum conversions? 
  • Is it better to market products in certain countries? 

Data science should be able to provide effective marketing solutions to enhance brand awareness, improve brand loyalty, and grow revenue.  


  1. Professional Services

Data Science is generating interest in the professional services sector, and data science jobs are sprouting up everywhere. Since analytics is becoming famous, major corporations and small businesses are looking for people to collect data, store it, guarantee its security, and use it appropriately. The methods for putting data science strategies into practice differ greatly depending on the business; therefore, different industries have unique approaches to gathering data, processing it, and displaying it.

Data scientists in professional services are primarily employed as data science consultants. With the aid of data science, these businesses can enhance their analytical capabilities, acquire skills, and understand how their company works, resulting in the attainment of corporate goals.


The professional services mainly include –

  • Finance and Insurance 
  • Healthcare 
  • Manufacturing 
  • Telecommunications and IT services  
  • Legal services
  • Accounting and bookkeeping
  • Marketing consultancy
  • Customer service)
  • Logistics 
  1. Cyber Security

According to Cybersecurity Ventures, worldwide cybercrime costs are expected to rise 15% each year through 2025, reaching USD 10.5 trillion annually by that time, up from USD 3 trillion in 2015. It’s worth noting that hackers nowadays employ more advanced artificial intelligence and deep learning algorithms to conduct their operations, known as cyber assaults. 

The widespread use of algorithms for malpractices has necessitated the cyber security sector’s adoption of data science and AI. Data scientists employ AI and machine learning algorithms to detect attack patterns and devise methods for preventing future assaults.

The computing procedures have gotten more practical and intelligent in comparison to previous information handling. It creates a climate for gathering data from relevant cybersecurity sources and analysis that corresponds with data-driven patterns. This marriage of data science and cybersecurity represents a shift from traditional security solutions such as user authentication, access control, cryptography, and firewalls toward systematic data management.

Data Science in Cyber Security helps to-

  • Detect malware, viruses, and cyber threats
  • Identify critical risks to company security
  • Analyse user behaviours and activity patterns
  • Respond to cyber threats in a more efficient manner
  • Provide an enhanced level of protection from emerging threats


  1. Mining, Quarrying, and Oil & Gas Extraction Sector

Technology’s most significant advantage in any sector is its ability to automate processes, and the oil industry is no exception. When it comes to a high-risk sector that must operate 24 hours a day, seven days a week, the use of data science in the mining and oil & gas industries is on the rise.

Data science is being increasingly used in industrial change and distribution, for example. Many geographic information systems (GIS) include probability components to identify areas with the most productive potential, as do many industrial data-driven solutions. Similarly, with Measurement During Drilling technology, it is possible to get terabytes of petrophysical and fluid data using data mining methods to characterise the reservoir better.


Data Science in Mining, Quarrying, and Oil and Gas Extraction Sector helps to-

  • Solve geological issues
  • Create accurate models of oil/ gas reservoirs
  • Optimise reservoir stimulation methods for ultimate recovery
  • Study complex good behaviours in real-time by acquiring petrophysical data
  • Analyse drilling data to determine the best option for drilling rigs, including rig type and location 
  • Conduct in-depth analysis of commercial aspects related to hydrocarbon production 
  • Improve management decisions at every stage in the process. 



The demand for Data science specialists in every industry is increasing, and the skills shortage of data scientists is an authentic problem. Businesses have been forced to rethink their recruitment strategies to attract talented Data Science professionals. Job roles within companies are being redefined as new positions arise that sit outside traditional job titles.

Organisations need to create new ways of mitigating the effects of this lack of talent. It means that there will be a robust future market for those who understand how to apply data science techniques and work at understanding and defining what kind of problems need solving and thus creating business value from the application of Data Science.

The availability of up to date, relevant and tailored data is critical for many Data Science applications. Recently, the industry has seen a massive surge in the need to link disparate datasets together as part of more expansive Big Data projects or as an input to more traditional analysis techniques. The information age is upon us, with abundant data readily available on just about any subject imaginable.

We are reaching a level where demand for specialist skills in machine learning and data mining is increasing – employers are looking to improve their competitive edge using analytics. As technology continues to advance at an incredible pace, so too will our hunger for talented individuals who can utilise it.

A Data Scientist’s average salary in India is ₹823,841, and this is predicted to increase with every passing year.


The uptrend in the demand for Data Science experts shows no sign of slowing. One of the most effective ways to get the best out of big data, analytics or machine learning is by hiring talent with excellent technical skills along with domain expertise.

With companies spending so much time, effort and money recruiting great workers, keeping them engaged – whether they are located at HQ or working remotely – has never been more critical.