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Data Scientist Salary 2024 - Based On Location, Role & Industry


Now that you are seeking critical information about Data Scientist Salary let me share some very positive news with you. Do you know that for four years in a row, a data scientist has been named the number one job in the U.S. by Glassdoor? The U.S. Bureau of Labor Statistics reports that the demand for data science skills will drive a 27.9 percent rise in employment in the field through 2026.

Many experts have stated data scientist is currently the most in-demand profession in the industry. According to the report, in 2020, the job requirements for data science and analytics are expected to increase by 364,000 openings to 2,720,000.

Data science experts are required in every industry —not just in technology. In fact. The 2011 McKinsey report on Big Data said that “The United States alone faces a shortage of 140,000 to 190,000 people with data analytical expertise and 1.5 million managers and analysts with the skills to understand and make decisions based on the analysis of Big Data.

Certified data science skills shortages are present in almost every large U.S. city. Nationally, there is a shortage of 151,717 people with data science skills, with particularly acute shortages in New York City (34,032 people), the San Francisco Bay Area (31,798 people), and Los Angeles (12,251 people).

Along with the US, there is a strong demand for Data Scientists in other regions also as per data from regional indeed sites (,,,, etc) UK: 1,100 jobs, France: 718 jobs, Germany: 900 jobs, India: 500 jobs. Glassdoor search for "Data Scientist" finds about 26000 jobs in the USA

How Much Is a Data Scientist Salary?

According to the U.S. Bureau of Labor Statistics, the average data scientist salary ranges around $100,560. As per, the data scientist salary average is $123,127 per year in the US. The key factor behind high data science salaries is the increasing dependence of organizations on big data and its power to drive smart business decisions. And because the supply of data professionals hasn’t yet caught up with demand, starting salaries for these positions remain high, especially for those who have an advanced degree in data science or a related field. 

Data Scientist Salary By Experience

According to O’Reilly’s 2016 Data Science Salary Survey, experience is one of the most important factors in a data scientist’s salary. For every year of experience, data science professionals make an average of $2,000 to $2,500 more.

A 2020 Burtch-Works study of data science salaries reported the latest salary trends based on experience:

  • Entry-level Data Scientist Salary: The median starting salary for a data scientist at entry-level remains high at $95,000.
  • Mid-level Data Scientist Salary: The median salary for a mid-level data scientist is $130,000. If this data scientist is also in a managerial role, the median salary rises to $195,000. 
  • Experienced Data Scientist Salary: Senior data scientist salary is $165,000, the median salary for experienced manager-level professionals is considerably higher at $250,000.

Data Scientist Salary by Job Title

In O’Reilly’s data science salary report, 45% of those surveyed hold the title of “data scientist.” Another 31% are in upper management roles. In general, the more a data science professional engages in managerial tasks—such as identification of business problems, project leads, identifying business problems to be solved with analytics, or communicating with external parties— and so have higher salaries.

data scientist salary

Source: O’Reilly Salary Data Science Salary Report, 2016

1) Data Scientist - Those with the job title of “Data Scientist” are generally experienced, and hold expert-level knowledge in data-driven organizations, according to Salary range: $85,000-$170,000.

2) Data Analyst - Data analysts work hands-on with data and tend to be at a point in their careers when they are focused on building up data science tools and skillsets. Entry-level salary: $50,000-$75,000 & Experienced salary: $65,000-$110,000.

3) Data Science/Analytics Manager - These professionals with the team under them have sharp technical and quantitative skills, and strong leadership and business aptitude. Salary range: $90,000-$140,000.

4) Business Intelligence Manager: The 2021 average Business Intelligence Manager salary in the US is $134479 as per They have proficiency in SAP BI, People management, Data warehouse, data mining, Cognos, Microstrategy, BI, SQL, Big data analytics, project management.

5) Data Architect: The national average salary for a Data Architect is $1,08,278 in the United States as per They have expertise in data management, Oracle DB, Data mining/Data warehouse, BI & Data modeling.

6) Business Intelligence consultant: As of Feb 6, 2021, the average annual pay for a Business Intelligence Consultant in the United States is $116,612 a year, which works out to be approximately $56.06 an hour. They hold expertise in Project Management, SAS, Data warehouse, BusinessObjects, MicroStrategy, BI, Cognos, SQL.

7) Business Intelligence Analyst: The national average salary for a Business Intelligence Analyst is $76,402 in the United States as per They specialize in data modelling/data warehouse, project management, BusinessObjects, BI, Cognos, business analysis, data mining, SQL.

8) Data Analyst: The average salary for a Data Analyst is $75171 per year in the United States. They work on data mining/data warehouse, data modeling, SAS, SQL, Statistical Analysis, DB Management & Reporting, data analysis.

Data Scientist Salary by Industry and Company Size

The industries with the highest data science salaries are:

  1. Cloud services, hosting, and CDN
  2. Search and social networking
  3. Banking and finance

data scientist salary

Source: O’Reilly Salary Data Science Salary Report, 2016

Perhaps not surprisingly, some of the highest-paid data scientists work at leading tech companies. Here are average salaries at several high-profile organizations:

  • Data Scientist salary Google : $152,856
  • Apple: $145,974
  • Twitter: $135,360
  • Facebook: $134,715
  • PayPal: $132,909
  • Airbnb: $127,852
  • Microsoft: $123,328

As far as company size, the larger the organization, the larger the salary. For example, in a company with at least 10,000 employees, a data scientist would likely earn a higher income than the same role at a company with less than 1,000 employees.

data scientist salary

Data Scientist Salary By Region

Data scientists’ salaries depend greatly on the region in which they live. The highest salaries are in California, as compared to the Pacific Northwest where we have fewer data scientists than most regions of the country, but it boasts the second-highest salaries. Data scientist salary in NYC is $1,13,156 as per scientist salary

Data Scientist Salary by Education

Data scientists are in huge demand but less in supply as it’s rare to find the right combination of education and skills. 

Data Scientist Salary, by Education (in U.S. $)


25th Quartile


75th Quartile

Bachelor's degree




Master's degree




Doctoral degree




Source: Burning Glass

Higher are the salaries when data scientists are equipped with new and emerging technologies and open-source tools, cloud computing, and data visualization. It’s not enough to simply know how to use these tools, however; it’s crucial that data scientists know how to use them to derive actionable insights that will improve their organization.

Also, data science positions require sharp business acumen, scientific curiosity, and strong leadership and communication skills. Having them will greatly affect salary. 

Data scientists with advanced degrees in quantitative disciplines such as data science, applied mathematics, statistics, computer science, engineering, economics, or operations research fetch higher salaries.

Factors That Affect Data Scientist Salary

A Data Scientist’s salary depends on several factors:

  • Experience
  • Job Title
  • Industry
  • Company Size
  • Region
  • Education

Tips For Negotiating Your Desired Data Scientist Salary

The secret to successful salary negotiation is often how you approach it, being proactive about research, and also implement during the process. Here’s what to keep in mind!

1) Do your salary research before negotiating

For winning the negotiation process, make sure to research salaries in the region/industry/job level you’re applying to. Figuring out your “market value” can be tricky, so look for various reports that will help you come up with a range. Hopefully, if you were evaluating a job offer, you took the time to assess the salary or salary range that the company was targeting for the role you’re applying to. Depending on the company there may not be too much room for negotiation, so doing your research will help. Be open to other perks that can help close the gap in average data scientist salary.

2) Approach the negotiation process tactfully

Negotiation is kind of the first interaction you have with the employer and also sets the tone for your employment. Make sure that if you decide to negotiate you’re prepared to say yes, otherwise you may burn bridges! If you’re already working at the company, keep in mind that you probably want to preserve a good, working relationship with your manager/boss regardless of how the negotiating process goes. Successful negotiation is all about the approach. Try to focus on asking for what’s important to you, explaining why, and showing why you’ve earned it, rather than demanding.

3) Be honest about what’s important to you

We all know that salary is one of the top motivation factors– but when you’re negotiating you’ll want to also keep in mind other factors that are important to you like wanting to have expertise in different tools in your role,  employment benefits so do ask about it. If you’re working with an external recruiter during the job search process, they should be able to help you navigate this process and ask questions that you might not want to. If you’re negotiating on your own, be transparent about your priorities ensuring the tone is cooperative.

4) Show that you’re a good fit for this specific role

The employer needs to see you are the best fit for the role and why you deserve the salary hike. Especially if you have specialized data science expertise, you should be able to point to experience and qualifications that make you an outstanding fit. Enhance your job description with your skillsets and experience. 

How Many 'Data Scientists' Are There?

Kaggle (now part of Google) is a platform for data science and analytics competitions and is claimed as the world’s largest community of active data scientists. In June 2017, the Kaggle community crossed 1 million members, and in 2018, they surpassed 2 million members. 

On LinkedIn, there are many groups dedicated to data science, here are three of the largest groups

Recently Added Data Scientist Jobs and Salaries





Data Scientist, Engineering

Mountain View, CA, USA


$1.1L - 230K per year

Data Scientist

Princeton, NJ, USA


$84K - 140K per year

Product Data Scientist 

San Francisco, CA, USA


Not disclosed

AI & Analytics Data Scientist

United States

Cognizant Technology Solutions

Not disclosed

Technical Skills sets For Data Scientist The Industry Is Looking for


Data scientists are highly educated, a very strong educational background and certification are required to develop the depth of knowledge necessary to be a data scientist. To become a data scientist and get a high salary as a data scientist salary entry-level, you could earn a Bachelor’s degree in Computer science, Social sciences, Physical sciences, and Statistics. The most common fields of study are Mathematics and Statistics (32%), followed by Computer Science (19%) and Engineering (16%). After your bachelor’s, you need a Master's degree or Ph.D. or certified online training platform to learn a special skill like how to use Hadoop or Big Data querying. 

R Programming

In-depth knowledge of these analytical tools is important. R is specifically designed for data science needs. You can use R to solve any problem you encounter in data science. In fact, 43% of data scientists are using R to solve statistical problems. However, R has a steep learning curve. Learn from our experts at JanBask Training

Hadoop Platform

A study carried out by CrowdFlower on 3490 LinkedIn data science jobs ranked Apache Hadoop as the second most important skill for a data scientist with a 49% rating.


40 percent of respondents surveyed by O'Reilly use Python as their major programming language. It is an essential technical skill as it helps understand various formats of data, create datasets, and much more.

SQL Database/Coding

You need to be proficient in SQL as a data scientist. SQL is specifically designed to help you access, communicate, work on data and fetch out valuable insights for the organization. 

Apache Spark

Apache spark helps data scientists prevent the loss of data in data science. Its speed and platform which makes it easy to carry out data science projects are the key strengths.

Data Visualization

Data scientists should have the acumen for visualization data, and quickly grasp insights that will help them to act on new business opportunities and stay ahead of competitions.

Non-Technical Skills That Can Increase Your Data Scientist Salary

Being Curious

A data scientist should be curious to grab knowledge and its implementation. As a data scientist, you need to be able to ask questions about data because data scientists spend about 80 percent of their time discovering and preparing data. Its fast-evolving pace needs a data scientist to be at top of industry trends.

Business Acumen

As a data scientist, you’ll need a solid understanding of the industry for which you are working, its challenges, and the solutions, in addition to identifying new ways the business should be leveraging its data.

Communication Skills

Working with stakeholders, multiple teams, working on unstructured data, driving insights, and communicating it in the most effective way is a day to day responsibility of a data scientist. Strong communication skills will help create a storyline around the data and how easily the other person can understand it.


Data scientists play a vital strategic role in an organization. They’re tasked with mining their firm’s data for strategic insights that stakeholders both internal and external are dependent upon. No wonder it’s a notably fast-growing profession with high pay packages and perks. Given you acquire the right skillsets and certification will land you to top job roles as a data scientist. The emphasis is now on skills and specialization, which allow professionals to truly stand out from the crowd. 


Q1) How can Data Scientists increase their salaries?

Ans. There are multiple factors that impact Data Scientist salary:

  • Change of industry: You may consider changing to an industry that is more competitive and willing to pay higher salaries. Social networking companies like Google and Facebook looking for skilled data scientists due to heavy dependence on data often pay premium salaries for data scientists.
  • Higher education: Data scientists who obtain a doctoral degree, certifications are generally able to qualify for more advanced positions and higher salaries.
  • Leadership roles: Senior data scientists oversee junior data scientists in addition to their regular responsibilities

Q2) How can I know if I am being paid fairly as a data scientist?

Ans. Doing proper research regarding job roles, what similar organizations are offering, checking out industry trends will give you insight into what salaries data scientists are grabbing. 

Q3) What skills are needed to be a data scientist?

Ans. A data scientist must have relevant soft and technical skills including:

  • R Programming
  • Machine learning
  • Hadoop platform
  • Python
  • SQL
  • Data visualization
  • Soft skills like team management, communication skills, adaptability, and curiosity to learn about new technologies.


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