The 13 Highest Paying Data Scientist Jobs (+ Who’s Hiring)

Data science is a field that encompasses several different disciplines. But all of these data science roles require strong analytical skills, technical knowledge, and the ability to glean actionable insights from troves of information. 

As more and more industries use innovative data applications—from the healthcare sector using data science to improve patient care and drug development to Spotify using music data for personalized recommendations—data professionals of all stripes are in high demand. And there are a plethora of diverse job opportunities that cater to a wide range of passions and interests.

Why Do Data Scientists Get Paid So Much?

Data science professions command high salaries because there’s not enough supply (the profession has nearly 20,000 open positions in the United States, according to US News) and their skills are in high demand.

Data scientists are seeing this demand because, in the past few years, a growing number of organizations have begun to see the importance of making data-driven decisions. Whether it’s e-commerce companies making forays into artificial intelligence or travel companies incorporating machine learning onto their platforms, data scientists are at the forefront of the latest tech revolution. 

Highest Paying Data Science Jobs

In the United States, data science professionals typically earn around $117,000 a year, according to Glassdoor. However, this can vary depending on several factors, including years of experience, level of education, industry, location, and area of specialization. For example, in major cities such as New York or San Francisco, data scientists can make as much as $180,000. Machine learning engineers often earn more than data analysts, and those who work in the consumer technology sector usually make more than those who work for governmental agencies, nonprofits, or healthcare organizations. 

Data Scientist

The responsibilities of data scientists can vary from company to company. Generally speaking, data scientists source and process the data that is available to a company. 

What You’ll Do

Some of the responsibilities of a data scientist include:
– Identifying sources of data and automating the process of retrieving that data
– Preprocessing unstructured and structured data so that analysts can use the information to find meaningful insights
– Developing machine learning algorithms and using analytics tools to identify patterns in data
– Building predictive models to forecast trends so that organizations can make important business decisions
– Analyzing data systems for efficiency, security, and optimization opportunities

What Skills You Need

Data scientists are skilled in the following areas:
– Wrangling massive amounts of data
– Coding in programming languages such as Python and SQL
– Fluency with statistics, probability, calculus (both single variable and multivariable), and linear algebra
– Strong communication and the ability to use data to tell a story

How Much You’ll Make

The average annual salary for a data scientist in the United States is around $117,000, according to Glassdoor.

Data Engineer

Data engineers build pipelines that funnel data from different sources. They focus on the production readiness of raw data and elements such as formats, resilience, scaling, data storage, and security.

What You’ll Do

Data engineering encompasses the following:
– Building free-flowing data pipelines that enable real-time analytics
– Writing complex queries to ensure data is easily accessible
– Creating and maintaining data management systems
– Creating data analytics tools for team members
– Formatting data so that it can be used by team members

What Skills You Need

Data engineers are skilled in the following areas:
– Programming languages such as Python, SQL, Java, and Scala
– A background in computer science, software engineering, or a related field
– Understanding data architectures and cloud computing
– Deep knowledge of automation and scripting
– Understanding ETL tools, data APIs, and distributed systems

How Much You’ll Make

The average annual salary for a data engineer in the United States is around $113,000, according to Glassdoor.

Data Architect

Data architects visualize and design an organization’s data management framework. They do this by assessing an organization’s data sources, then designing a plan to integrate, centralize, and maintain gathered data. 

What You’ll Do

Data architects are responsible for the following:
– Inventorying the data needs of an organization
– Researching opportunities for new data acquisition
– Assessing existing data management methods and technologies
– Creating an end-to-end vision for how data will flow through an organization
– Designing, documenting, and deploying database architectures
– Maintaining database development standards

What Skills You Need

Data architects are skills in the following areas:

– Programming languages such as Python, Java, C++, and Perl
– Hadoop and NoSQL databases
– Predictive modeling, natural language processing, and text analysis
– Application server software such as Oracle, user interface and query software such as IBM DB2, and database management software such as Microsoft SQL Server
– Datamining
– Data modeling tools such as Visio, ERWin, and Enterprise Architect

How Much You’ll Make

The average annual salary for a data architect in the United States is around $152,000, according to Glassdoor. 

Data Modeler

A data modeler translates real-world business needs into data models. They work closely with data architects to create conceptual, logical, and physical data models. They support application teams when designing databases and collaborate with data governance teams for compliance.

What You’ll Do

Data modelers have the following responsibilities:
– Transforming business information into models so that complex data can be used by computer systems
– Developing and validating data models to ensure they meet an organization’s needs
– Evaluating existing data systems
– Ensuring data coding consistency within a system
– Updating and optimizing metadata models

What Skills You Need

Data modelers are skilled in the following areas:
– Programming languages such as SQL
– Deep knowledge of metadata management
– Experience with physical and relational data modeling
– Interpersonal and communication skills
– Statistical analysis and mathematics

How Much You’ll Make

The average annual salary for a data modeler in the United States is around $106,000, according to Glassdoor. 

Big Data Engineer

Big data engineering focuses on the infrastructure that allows people to collect and organize enormous amounts of data. This makes billions of clicks, taps, likes, swipes, shares, and purchases usable for data analysis. They do this through building data pipelines, designing and managing data infrastructures, handling data storage, and focusing on the ETL (Extract, Transform, Load) process.

What You’ll Do

Big data engineers make large amounts of user data manageable in the following ways:

– Building data pipelines
– Designing and managing data infrastructures such as big data frameworks and databases
– Handling data storage
– Working on the ETL (Extract, Transform, Load) process

What Skills You Need

Big data engineers are skilled in the following areas:
– Programming languages such as Python, SQL, Java, and C++
– Automation and scripting
– ETL tools and data APIs
– Machine learning algorithms
– Data warehousing solutions
– Communication and interpersonal skills

How Much You’ll Make

The average annual salary for a big data engineer in the United States is around $125,000, according to Glassdoor. 

Machine Learning Engineer

A machine learning (ML) engineer is a programmer who designs self-running software that uses data and automates predictive models. ML engineers bridge the gap between data and software, creating programs that allow machines to function without direct human assistance.

What You’ll Do

ML engineers are usually expected to perform the following functions:
– Designing machine learning systems
– Researching and implementing machine learning algorithms and tools
– Verifying data quality
– Collaborating with managers to determine machine learning objectives
– Solving complex problems with multilayered data sets

What Skills You Need

Machine learning engineers are skilled in the following areas:
– Programming languages such as Python, Java, SQL, and R
– Computational linguistics, data analytics, artificial intelligence, and deep learning
– Machine learning frameworks, algorithm libraries, and software architecture
– Designing predictive models
– Mathematics, statistics, and algorithms
– Strong communication

How Much You’ll Make

The average annual salary for a machine learning engineer in the United States is around $123,000, according to Glassdoor. 

AI Engineer

Machine Learning is a subset of data science. Although machine learning engineers and AI engineers do some of the same tasks, artificial intelligence (AI) engineering places a greater emphasis on ​​the development of systems and machines that mimic human cognitive function, which makes them more adept at problem-solving. 

What You’ll Do

Some of the responsibilities of AI engineers include:
– Developing, testing, and deploying AI models
– Building data ingestion infrastructure
– Evaluating and comparing algorithm performance
– Automating infrastructure used by the data science team
– Transforming machine learning models into APIs

What Skills You Need

AI engineers are skilled in the following areas:
– Programming languages such as Python, SQL, Java, C++, and R
– Statistics, applied mathematics, and algorithms
– Natural language processing
– Deep learning and neural networks
– Strong communication
– Creative problem-solving

How Much You’ll Make

The average annual salary for an AI engineer in the United States is around $118,000, according to Glassdoor. 

Enterprise Architect

An enterprise architect is an IT professional who oversees an organization’s networks and services. They update systems throughout the company, replace hardware or software, and determine what products and services best support teams within an organization. 

What You’ll Do

Enterprise architects typically have the following responsibilities:
– Standardizing and organizing a company’s IT infrastructure
– Creating a map of IT assets and business processes
– Updating legacy systems
– Advising management on information integration strategies
– Ensuring that an organization’s enterprise architecture aligns with its goals

What Skills You Need

Some of the required skills of enterprise architects include:
– Project management capabilities
– Understanding business models
– Strong knowledge of IT processes
– Strong leadership skills
– Clear written and verbal communication
– Analytical thinking and problem-solving

How Much You’ll Make

The average annual salary for an enterprise architect in the United States is around $164,000, according to Glassdoor.

Business Intelligence Analyst

Business intelligence (BI) analysts leverage their data for decision-making. They collaborate with business teams to understand their needs, review data, and write finance and market intelligence reports.

What You’ll Do

Some of the responsibilities of BI analysts include:
– Studying industry trends
– Analyzing company data to identify trends that could affect an organization’s business strategy
– Using data to develop action plans that help an organization grow and improve its business strategy
– Preparing analytical reports to share data findings with stakeholders

What Skills You Need

Skills required of business intelligence analysts include:
– Data preparation
– Data mining
– Statistical analysis
– Descriptive analysis
– Data visualization
– Understanding of business models

How Much You’ll Make

• The average annual salary for a business intelligence analyst in the United States is around $87,000, according to Glassdoor. 

NLP Engineer

Natural language processing engineers build systems and devices that can understand human language. A subset of artificial intelligence and machine learning, NLP engineers operate at the intersection of computer science, information science, AI, and linguistics. 

What You’ll Do

Some of the responsibilities of NLP engineers include:
– Designing NLP systems
– Training and testing NLP models
– Defining appropriate datasets for language learning
– Finding and implementing the right algorithms for NLP tasks
– Identifying text representations to transform natural language into useful features

What Skills You Need

Some of the required skills of NLP engineers include:
– Knowledge of programming languages such as Python, Java, and R
– Strong understanding of data modeling, data structures, text representation, and semantic extraction techniques
– Strong understanding of statistics and classification algorithms
– Analytical and problem-solving skills
– Effective written and verbal communication

How Much You’ll Make

The average annual salary for an NLP engineer in the United States is around $88,000, according to Glassdoor.

Database Manager

Database managers are often confused with database administrators, but their roles are different. While the former creates, updates, and deletes databases, a database manager maintains database results and performance. Database managers also maintain the safety and security of an organization’s databases. 

What You’ll Do

Database managers have the following responsibilities:
– Optimizing database tools and services
– Monitoring database performance and implementing improvements
– Conducting diagnostic tests and evaluating performance metrics
– Testing for bugs and security flaws
– Restoring lost data
– Supervising database development teams and administrators

What Skills You Need

Some of the required skills for database managers include:
– Deep knowledge of database technologies
– Strong communication and interpersonal skills
– Leadership and management skills
– Strong organization and attention to detail
– Analytical problem-solving skills

How Much You’ll Make

The average annual salary for a database manager in the United States is around $76,000, according to Glassdoor.

Database Developer

Also known as database designers or programmers, database developers design, build, and update databases.

What You’ll Do

Database developers are responsible for the following:
– Designing and developing databases
– Evaluating databases to ensure they meet an organization’s standards
– Creating storage and retrieval systems
– Troubleshooting database problems and solving malfunctions
– Providing users with access and permissions
– Maintaining database security

What Skills You Need

Database developers typically have the following skills:
– In-depth knowledge of current database processes
– Experience with BTL and business intelligence tools
– Knowledge of database objects such as indexes, views, statistics, and tables
– Programming languages such as SQL
– Data modeling
– Schema creation
– Familiarity with NoSQL database systems such as MongoDB and CouchDB

How Much You’ll Make

The average annual salary for a database developer in the United States is around $97,000, according to Glassdoor.

Data Analyst

A stepping stone into a data science career, data analysts identify trends, patterns, and relationships within data to inform business decisions. Data analysts mine data, organize insightful findings, build visualizations, and present reports to stakeholders. 

What You’ll Do

The responsibilities of data analysts fall into three categories:
– Mining data to pull information from primary and secondary sources
– Data cleaning to rid the data of errors and discrepancies, and to glean valuable insights through the identification of patterns, relationships, and trends
– Data visualization so that the information is easily accessible by stakeholders. 

What Skills You’ll Need

Data analyst skills include:
– Programming languages such as SQL, Python, and R
– Familiarity with data analytics tools such as Tableau, Google Analytics, Jupyter, Amazon Web Services, and Microsoft Excel
– Data mining and cleaning
– Data warehousing
– Data visualization
– Strong communication
– Creative and analytical thinking

How Much You’ll Make

The average annual salary for a data analyst in the United States is around $74,000, according to Glassdoor.

Highest Paying Data Science Companies

The more a company relies on data, the more it tends to pay its data scientists. Some of the highest-paying data science companies are social networking sites (who gather troves of user data), e-commerce platforms (who track billions of data points on consumer behavior), and real-time services (which depend on data to be responsive to customers). 

Amazon

Amazon’s data scientists work across all of its verticals, from parsing consumer purchase data on its e-commerce platform, to analyzing user behavior for its advertising division.

The average base salary for an Amazon data scientist is around $137,000, according to Glassdoor, although Amazon employees often make much more. In 2022, Amazon raised its base pay salary cap to $350,000 for corporate and tech employees, citing competition for tech talent. 

Uber

Uber’s data scientists work in product analytics (e.g. ensuring the accuracy of the maps and geolocation technologies), finance and operations (e.g. using data to help the company with its financial planning and competitive strategy), and marketing (e.g. drawing on analytical insights to help improve growth, brand awareness, customer retention, and engagement).

The average base salary for a Uber data scientist is around $147,000, according to Glassdoor. 

Meta

Meta’s data scientists work on products such as Facebook, Instagram, Oculus, Messenger, and WhatsApp. A data scientist focused on Instagram might help its monetization division drive a long-term strategy for revenue sharing. A business analyst at WhatsApp might collaborate with the sales and marketing teams to identify opportunities for user growth. And a machine learning engineer at Facebook might work on fraud detection technology.

The average base salary for a data scientist at Meta is around $152,000, according to Glassdoor. As one of the highest-paying technology companies in the world, it’s not unusual for data science professionals to make upwards of $200,000 at Meta. 

Airbnb

Airbnb’s data scientists work on a range of products and features, from fraud prevention to helping set rental prices. As the company grows, so does its demand for data science professionals. Airbnb currently has dozens of open roles for data scientists, machine learning engineers, and analysts. 

The average base salary for Airbnb data scientists is around $188,000, according to Glassdoor.

Apple

With more than 900 million active iPhones in the world, Apple is a data-collecting juggernaut. The company’s data science professionals work in all of its divisions, including hardware, software, music, and entertainment services.

The average base salary for Apple data scientists is around $158,000, according to Glassdoor. 

Booz Allen

Data scientists working for consulting firm Booz Allen are exposed to a range of clients and challenges, from helping commercial clients improve their cybersecurity, to assisting military clients. 

The average base salary for Booz Allen data scientists is around $94,000, according to Glassdoor. 

Microsoft

Microsoft’s size, reach, and product diversity mean that its data scientists get to solve a broad range of problems, from improving Microsoft Cloud to preventing bias in its language technologies.

The average base salary for Microsoft data scientists is around $139,000, according to Glassdoor. 

How To Increase Your Current Data Science salary Expand Your Toolset

Expand Your Toolset

The number of tools that a data science professional has mastered can affect their compensation, according to O’Reilly’s Data Science Survey. Some salary-boosting toolsets include Apache Spark, Scala, and D3, which can add upwards of $15,000 to a compensation package. Familiarity with cloud computing will also boost salaries, with survey respondents who use Amazon Elastic MapReduce getting a salary boost of about $6,000.

O’Reilly also noted that those who used 15 or more tools could make up to $30,000 more than those who just used 10 to 14. There is a premium associated with mastering a variety of tools.

Change Industries

Where you choose to work can determine your salary. The O’Reilly Salary Survey found that the highest salaries went to data scientists in search/social networking companies, which makes sense given the amount of valuable data those companies can access (think LinkedIn, Meta, or Google).

It’s important to note that companies like Meta and LinkedIn also offer generous stock incentive bonuses, which easily add about $40,000 to $50,000 more when it comes to compensation. 

Consider a New Location

Most people think of Silicon Valley as the region with the highest data science salaries. This is somewhat true. Payscale reports a 23% salary increase for workers in Mountain View, where Google and LinkedIn are headquartered. The O’Reilly report also infers that living in California is worth an extra $16,000 in salary.

But don’t forget to factor in the cost of living and state tax rates. For example, San Francisco is not where you can make the most as a data scientist. Neighboring San Jose has a lower cost of living and higher salary differential. In fact, when adjusting for cost of living and state taxes, Seattle trumps San Francisco. Likewise, cities such as Austin have lower base salaries for data scientists, but its low cost of living and no state taxes makes Austin comparable to other tech hubs.

Get a New Degree or Certification

In the O’Reilly survey, having a Master’s degree is correlated with a $1,000 a year salary increase. Adding a Ph.D. degree is correlated with a $9,000 yearly salary increase. However, a Ph.D. can quickly become a massive time investment (with an average of 8.2 years from start to dissertation), and if you spent that time gaining five years of experience in data science, you’d double the return on your annual salary. 

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