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HomeBlogData ScienceTop 12 Highest Paying Data Science Jobs in 2024 [With Salary]
Data Science, with its interdisciplinary approach, combines statistics, computer science, and domain knowledge and has opened up a world of exciting and lucrative career opportunities for professionals with the right skills and expertise. The market is flooding with the highest paying data science jobs. But which data science jobs pay the most? From Silicon Valley to Wall Street, from healthcare to e-commerce, data scientists are highly valued and well-compensated in various industries and sectors. According to Glassdoor, the average annual pay of a data scientist is USD 126,683. In this blog post, we will look at some of the world's highest paying data science jobs, what they entail, and what skills and experience you need to land them.
Data science is an interdisciplinary academic domain that utilizes scientific methods, scientific computing, statistics, algorithms, processes, and systems to extrapolate or extract knowledge and insights from unstructured, structured, and noisy data.
Data science also blends expertise from various application domains, such as natural sciences, information technology, and medicine. It encompasses a broad range of facets and can refer to data science as a science, a research method, a research paradigm, workflow, discipline, workflow, and profession.
If you aim to bag the data scientist highest salary, you must be skilled with the above skills. If you are lacking those skills and want to get training, get to know the Data Science course fee and go for the program.
Studies suggest the data scientists' employment rate will surge to 36% by 2031. 49% of the job ads on LinkedIn are in the Tech and IT industry. While only 33% of job ads specifically demand a data science degree, the highly sought-after technical skills are SQL and Python. Below we have curated a list of the highest paying data science jobs:
High Paying Data Science Jobs | Salary (Per year) |
Data Architect | $165,583 |
Data Scientist | $126,694 |
Data Modeler | $126,811 |
Big Data Engineer | $120,269 |
AI Engineer | $128,280 |
Machine Learning Engineer | $132,910 |
Enterprise Architect | $215,617 |
Business Intelligent Analyst | $87,646 |
Database Manager | $80,949 |
NLP Engineer | $137,757 |
Data Analyst | $70,210 |
Database Developer | $86,864 |
Source: Glassdoor, Indeed
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Data architects play a crucial role in designing an organization's data management framework by assessing data sources and integrating them into a centralized plan.
A data scientist is a professional who uses scientific methods, algorithms, and systems to extract insights from data.
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Data modelers are professionals who translate business requirements into data models with data architects for computer systems to utilize complex data.
Big data engineers focus on the infrastructure for collecting and organizing vast amounts of data, building data pipelines, and designing data infrastructures. They manage data storage and the ETL process.
One of the highest paying data science jobs. Artificial Intelligence (AI) engineering involves developing systems and machines that mimic human cognitive functions to solve complex problems.
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A Machine Learning (ML) engineer designs self-running software using data to automate predictive models and enable machines to work independently. They bridge the gap between data and software.
If you are looking for a data scientist highest salary job, it is of an enterprise architect. An enterprise architect manages an organization's networks and services, updates systems, and determines optimal products and services for teams.
BI analysts use data to help businesses make informed decisions, collaborating with teams to analyze data and create financial and market reports.
Database managers are different from database administrators, responsible for managing database results and performance and ensuring data security.
An NLP (Natural Language Processing) Engineer is a professional who specializes in developing algorithms and applications that allow computers to understand and interpret human language.
A data analyst is a professional who analyzes and interprets complex data to inform business decisions. Data analysts identify patterns, relationships, and trends in data to inform business decisions using data mining, organization, visualization, and reporting.
A database developer is a professional who designs, implements, and maintains computer databases.
There are several top companies hiring for data science roles around the world, including tech giants like Google, Amazon, and Microsoft. These companies are looking for talented data scientists to help them make sense of large amounts of data and develop predictive models to inform business decisions. Explore opportunities for the highest paying jobs in Data Science with these industry leaders.
Company | Job Roles | Highest Annual Salary |
Amazon | Data Scientist | USD 350,000/ yr |
Intel | Big Data Engineer | USD 220,000/ yr |
IBM | Data Scientist | USD 230,000/ yr |
Uber | Data Scientist | USD 250,000/ yr |
Microsoft | Data Scientist | USD 325,000/ yr |
Machine Learning Engineer | USD 285,000/ yr | |
Data Scientist | USD 275,000/ yr | |
Apple | Data Scientist | USD 260,000/ yr |
Airbnb | Data Scientist | USD 240,000/ yr |
Tesla | Machine Learning Engineer | USD 190,000/ yr |
PayPal | Data Scientist | USD 160,000/ yr |
Yelp | Data Scientist | USD 155,000/ yr |
Lyft | Data Scientist | USD 175,000/ yr |
Square | Data Scientist | USD 150,000/ yr |
Data Scientist | USD 200,000/ yr | |
Oracle | Data Scientist | USD 170,000/ yr |
Data Scientist | USD 180,000/ yr | |
Nvidia | Deep Learning Engineer | USD 165,000/ yr |
The demand for data science professionals is growing rapidly in various industries worldwide, offering competitive salaries ranging from $70,000 to $150,000. Top recruiters include Amazon, Google, Microsoft, and industries like finance, healthcare, and e-commerce.
Given below are some top industries offering the highest paying data science jobs:
Industry | Roles | Salary Range (USD) |
Technology | Data Scientist, Data Analyst, Data Engineer | $70,000 - 200,000+ |
Finance and Banking | Quantitative Analyst, Risk Analyst, Data Analyst | $70,000 - 130,000+ |
Healthcare | Clinical Data Analyst, Health Data Analyst | $65,000 - 120,000+ |
E-commerce and Retail | Data Scientist, Marketing Analyst, Business Analyst | $60,000 - 200,000+ |
Telecommunications | Network Data Analyst, Business Intelligence Analyst | $70,000 - 180,000+ |
Energy and Utilities | Energy Data Analyst, Power Systems Engineer | $70,000 - 150,000+ |
Education | Data Analyst, Research Analyst | $50,000 - 120,000+ |
Government and Defence | Intelligence Analyst, Cybersecurity Analyst | $60,000 - 200,000+ |
If you want to land the highest paying data science job, then go for the top Data Science Bootcamps program and become a sought-after data scientist.
Given below are some top cities in the top nations offering the high paying jobs in data science:
A. United States | |
New York City | USD 130,706/ yr |
Chicago, IL | USD 134,303/ yr |
Los Angeles, CA | USD 126,169/ yr |
San Francisco, CA | USD 142,676/ yr |
B. India | |
Bengaluru | USD 24,488.38/ yr |
Hyderabad | USD 14,233.87/ yr |
Mumbai | USD 13,762.47/ yr |
Chennai | USD 13,786.96/ yr |
C. United Kingdom | |
London | USD 78,296.02/ yr |
Northern Ireland | USD 42,897.57/ yr |
Wales | USD 45,520.23/ yr |
Bristol | USD 63,237.15/ yr |
D. Singapore | |
Singapore | USD 163,307.69/ yr |
Jurong East | USD 86,027.67/ yr |
Hougang | USD 80,409.46/ yr |
Outram | USD 103,184.91/ yr |
If you're looking to boost your salary as a data scientist, here are a few tips:
Data science is set to grow immensely in the coming years. In 2022, the global market for data science market is estimated at USD 10.15 billion, and is expected to reach USD 29.98 billion by 2029, according to a report by Mordor Intel.
This growth is due to more businesses needing data to make better decisions and the rise of technologies like artificial intelligence and machine learning.
Industries such as healthcare, finance, and retail are using data science to improve their services and stay competitive. As these technologies become more common, the need for skilled data scientists will keep rising, creating highest paying data science jobs for professionals.
Couldn't wonder why data scientists get such high pay? Well, there's more than one reason for that:
If you have the right skills and expertise, there has never been a better time to pursue a career in data science. Applied Data Science with Python will support you in creating robust predictive models with advanced statistics and learning Python.
There are several online job search platforms to help data scientists find job opportunities. These tools can help data scientists search for job openings, create job alerts, and enhancing prospects for landing the highest paying data scientist jobs.
We have enlisted the tools and portals below:
We have discussed the top 12 highest paying data science jobs with salaries. It is clear that data science is an exciting and highly rewarding field with many lucrative opportunities for those with the right skills and mindset. According to Glassdoor, the average annual salary for a data scientist in the United States is over USD 110,000, with top earners making well over USD 150,000. Besides the data scientist highest salary, data science professionals enjoy a diverse range of job opportunities across many industries, from tech and finance to healthcare and retail. As more businesses recognize the value of data-driven insights, the demand for skilled data scientists is only expected to increase in the coming years.
According to Glassdoor, the highest salary of data scientists is USD 206,000.
In the United States, a data scientist earns an average pay of USD 126,683.
Yes, the data scientist job is one of the highest-paying jobs recently with an average annual pay ranging from USD 99,000 to USD 164,000.
It totally depends on your employer. You may have to work 40 hours per week or more.
They can upgrade their skill, gain more experience and relevant certifications, complete projects timely, add value to the business, and consider professional development opportunities.
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