Data Scientist Salary Reports From Around the World

Data has become the force that guides our lives and determines how we think. This is true for both individuals and organisations. New-age technologies like Artificial Intelligence (AI), Machine Learning (ML) and Data Science have grown remarkably and branched out into different specialities that make various real-life applications possible. According to a report by the Bureau of Labour Statistics (BLS), data science and information research scientist jobs will see a 14% growth through 2028.

India is the world’s second-largest recruiter of professionals in the field of data science and analytics with over 50,000 data science professionals, second only to the United States. There is a large amount of data that is generated and collected on a daily basis. Global organisations are looking for ways to process, access and analyse this data to derive actionable insights for their businesses. The demand for data scientists is rapidly growing in large enterprises, e-commerce companies and even startups. These organisations are ready to pay a hefty salary to data scientists and data professionals today.

Data Scientists - Who They Are And What They Do:

Data Science is an interdisciplinary field. It uses scientific methodologies, processes, algorithms and systems to derive insights and knowledge from a sea of structured and unstructured data. It is closely linked to data mining, machine learning and big data.

Data scientist is among the most coveted job titles today, both for recruiters and for IT professionals. Data Scientists are analytical experts in data who are highly skilled in solving complex insight derivation and data-related problems while identifying and solving new problems on a regular basis. They bring together the best of the two worlds of IT and business. Their skills are highly developed in computer science, mathematics and trend analysis.

Prerequisites to Become a Data Scientist:

Are you looking to join the field of data science? There are many different roles you can take up as long as you meet the technical and general prerequisites for the field:

  •  Knowledge of algorithms, statistics, mathematics and machine learning
  • Programming languages like R, Python, SQL, SAS and Hive
  • Business understanding and an aptitude to ask the right questions
  • Communication skills to help relay the results to the rest of your team and stakeholders

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Job Roles In Data Science:

1. Data Scientist:

Data science in this regard is the implementation of statistics through programming. R and Python are the two main programming languages that have proven highly effective in sorting out data for generic and highly specific requirements. In the Indian market, Python programmers for data science get paid more than both software developers and DevOps programmers. This is because the demand for data cleaning and processing professionals is growing rapidly due to the large amounts of consumer data that needs to be gathered.

The main responsibilities of data scientists are

  • Gathering huge volumes of structured and unstructured data and deriving actionable insights
  • Identifying data-analytics solutions that have the most potential to drive organisational growth
  • Using text analytics, machine learning, deep learning and other analytical techniques to analyse data and identify patterns
  • Encouraging a data-driven approach to solving complex business problems

2. Data Engineer:

A data engineer’s primary function is to design and engineer a reliable infrastructure to transform data into formats that can be used by data scientists. They build scalable pipelines and channels to convert unstructured and semi-structured data into usable formats, and also identify meaningful trends in large datasets.

Data engineers are as vital to an organisation as data scientists. They don’t come into the limelight because they don’t have a direct link to the end product of the analysis. The main responsibilities of a data engineer are

  • Integrating, consolidating and cleansing data from multiple sources
  • Developing the infrastructure required for optimal extraction, transformation and loading of data from various sources using SQL, AWS and other big data technologies.
  • Develop, construct, test and maintain data architectures.

3. Data Analysts:

Data analysts are professionals who take numbers, statistics and figures and convert them into colloquial terms that everyone can understand. With the increasing amount of data that is generated on a daily basis, organisations across industries are always on the lookout for data analysts.

This job role is the perfect choice for those who are skilled in mathematics, statistics, computer science, or business backgrounds. You need to be fluent in languages like SQL and Python to extract relevant insights, and also know how to derive insights and channel them into reports and visualisations.

The main responsibilities are

  • Analysing and mining business data to identify patterns from several data points.
  • Working with customer-centric algorithm models and personalising them to fit individual requirements.
  • Creating and deploying custom models to find answers for business problems and marketing strategies
  • Mapping and tracing data from multiple systems to solve specific business problems
  • Writing SQL queries to extract data from data warehouses and find answers to complex business problems
  • Applying statistical analysis methods to conduct consumer data research and analytics

Additional Read: 20 Most Popular Data Science Interview Questions & Answers

Data Scientist Salary In India and Other Countries

There are several factors that affect the salary of a data scientist. These are

  1. Data Scientist Salary by Experience -
    Data scientists at an entry-level start off at a basic salary, but thanks to the exponential evolution and growing demand for data scientists, there are many opportunities for significant growth. Data scientists both in India and abroad can start at a basic level and then have the option to branch out into more specific roles.

An entry-level data scientist is freshly out of college with no prior experience. Their focus is on learning and skill-practising. According to ZipRecruiter, their annual salary is estimated at $69,000, while a mid-level data scientist earns about $89,000.
An experienced data scientist is a data pro who has dedicated his/ her life to the data science profession. They earn about $162,000 a year, while an experienced manager-level data scientist easily earns about $184,000 a year.

  1. Data Scientist Salary by Location -
    Salaries of data scientists also vary by the geography of the market, depending on demand.

India is the world’s second-largest job market for data scientists, which means there are more opportunities and recruiters for Indian data scientists than almost every other country in the world. According to PayScale, the average data scientist earns ₹7,08,012 a year. This is higher than the average pay of many other professions in the IT industry.
The average salary of a data scientist in the US is $96,106. This is also a very high number, which is justified given that the US is the largest recruiter market for data scientists.

The salary figures vary by country. According to LinkedIn, the average data scientist in Singapore earns SGD93,000 per annum while data scientists in Mexico earn MX$3,96,000 per year.

  1. Data Scientist Salary by Organisation -
    Different organisations have different pay scales for the data science and analysis departments. While they largely follow a predefined price range, the scale of the organisation determines whether you get the upper or lower limit of that range.

Data science as a career path is not going anywhere any time soon. Opportunities will continue to grow for those who choose data science as a career path. Take the first step, enroll for a data science certification program today.

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Armin Vans
Aarav Goel has top education industry knowledge with 4 years of experience. Being a passionate blogger also does blogging on the technology niche.


Nicely explained .. thanks for all the information


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