7 Data Science Specializations: Learn and Compare

Benefits of Specializing in an Area in Data Science

In an online master’s in data science specialization, students acquire specific knowledge and practice skills that may benefit their future careers.

If your undergraduate degree is in data science, mathematics, computer science or a related field, compare the options that build on that background. Choosing a specialization allows you to focus on the aspects of data science that interest you the most, such as artificial intelligence and machine learning.

Data Science Specializations

Data science is becoming more integrated with business, science and government. Data science specialities enable you to build the skills you may need to help your organization succeed. The O*NET OnLine profiles cited in this section describe occupations rather than degree programs, so they show what each role involves, not which roles a particular track prepares its graduates for.

Business Analytics and Intelligence

Learning Outcomes: Look for a business analytics and intelligence specialization that teaches you how to use data to make business decisions, interpret and relay data information to stakeholders and help solve problems in your organization.

Specific Skills and Knowledge: Check whether the course list covers:

• Mathematical process skills
• Statistical analysis methods
• Database management
• Regression modeling
• Reports production and presentation

Possible Careers: Earning a master’s in business analytics or a master’s in data science with a track in business analytics may prepare you for positions such as:

• Business intelligence analyst
• Market research analyst
• Business analyst
• Marketing specialist

O*NET OnLine, the U.S. Department of Labor’s occupational database, describes business intelligence analysts as producing financial and market intelligence by querying data repositories and generating periodic reports. Its profiles also list business analyst as a reported job title for management analysts and market research analyst as one for market research analysts and marketing specialists.

Prerequisites: Check whether the program expects prior coursework in programming, statistics and calculus.

Data Science With a Computational Track

Learning Outcomes: Look for a computational data science specialty that focuses on the foundations of data science, including data systems, algorithms, data analytics and big data infrastructure.

Specific Skills and Knowledge: Check whether the course list covers:

• Mechanics of data science tactics and methodologies
• Technological theory
• Engineering
• Statistics
• Algorithms and data structures
• Information retrieval

Possible Careers: After completing this master’s in data science with a specialization in computational data science, you may be able to pursue positions in the following fields:

• Retail
• Healthcare
• Insurance
• Finance and banking

U.S. Bureau of Labor Statistics Occupational Employment and Wage Statistics (OEWS) estimates for May 2025 show data scientists employed in retail trade, health care and social assistance and finance and insurance, including credit intermediation and related activities.

Prerequisites: Check whether the track expects prior college-level coursework in calculus and programming.

If you are interested in computer science specifically, you may also consider a traditional or online master’s in computer science.

Data Engineering and Warehousing

Learning Outcomes: Look for a program that teaches the methods and technologies used to manage big data warehouses, along with engineering and problem-solving skills based in big data solutions.

Specific Skills and Knowledge: Check whether a data engineering specialization covers:

• Optimizing data collection and storage
• Processing and analyzing data
• Reporting and visualizing statistics and patterns
• Building and testing models to manage large quantities of data
• Learning programming languages

Possible Careers: This specialization may prepare you for roles such as:

• Computer systems analyst
• Network analyst
• Data scientist
• Data warehouse analyst
• Data engineer
• Database manager

O*NET OnLine lists computer systems analyst as a reported job title for computer systems analysts, network analyst for network and computer systems administrators, data warehouse analyst for data warehousing specialists, database manager for database administrators and data engineer for database architects, and it profiles data scientists as an occupation of their own.

Prerequisites: Before applying, check whether the program asks for a bachelor’s degree in a related field such as computer science, electrical or computer engineering, mathematics, statistics or information systems.

Database Management and Architecture

Learning Outcomes: Look for a program that teaches you how to design and manage big data systems, as well as how to curate and process data. These skills may be useful for helping others in your organization access and interpret information.

Specific Skills and Knowledge: Check whether a database management specialization covers skills such as:

• Database design and management
• Data warehousing
• Business intelligence
• Big data systems engineering
• Advanced architecture design
• Business analysis

Possible Careers: After finishing this specialization, you may be prepared for these careers:

• Data engineer
• Database architect
• Information architect
• Database administrator

In O*NET OnLine’s profile of database architects, reported job titles include data architect, data engineer and information architect, and the work includes modeling, designing and building large relational databases or data warehouses. Its profile of database administrators lists database administrator among reported job titles.

Prerequisites: Check whether the program asks for a bachelor’s degree in data science or a related field.

Data Mining and Statistical Analysis

Learning Outcomes: Look for a specialization that combines mathematical and statistical study with in-depth computational and data analytic training.

Specific Skills and Knowledge: Check whether the course list covers:

• Mathematical and applied statistics
• Data management
• Analysis and model-building with large datasets and databases
• Statistical computing
• Statistical learning

Possible Careers: A specialization in data mining and statistical analysis may prepare you to be a:

• Data mining analyst
• Quantitative analyst
• Marketing analyst
• Data engineer
• Data analyst

O*NET OnLine describes data scientists as applying data mining, data modeling, natural language processing and machine learning to large structured and unstructured datasets, then visualizing, interpreting and reporting what they find. Its profiles also list quantitative analyst as a reported job title for financial quantitative analysts and data engineer as one for database architects.

Prerequisites: Check whether the program expects prior coursework in calculus, algebra, mathematical statistics and programming.

Machine Learning

Learning Outcomes: Look for a program that teaches methods for using advanced computational algorithms to expand cognitive functions and advance automation, and that shows how algorithms and models may be used to solve complex problems.

Specific Skills and Knowledge: Check whether a data science machine learning specialization covers skills such as:

• Applied statistics
• Data mining
• Information visualization
• Natural language processing
• Data and network security
• Pattern recognition

Possible Careers: Positions that you may be able to pursue include:

• Software engineer
• Statistician
• Data architect
• Application developer
• Programmer

In O*NET OnLine, software engineer and application developer are reported job titles for software developers, programmer is one for computer programmers, statistician is one for statisticians and data architect is one for database architects.

Prerequisites: Check whether the program asks for a bachelor’s degree in statistics or applied mathematics, or for college-level coursework in subjects such as statistics, calculus and programming.

Managerial Data Science

Learning Outcomes: Look for a program that teaches methods for managing data science projects, and check how it balances technical, interpersonal and project management skills.

Specific Skills and Knowledge: Check whether a managerial data science track covers topics such as:

• Database systems
• Programming languages
• Communication
• General management
• Specific business domain knowledge

Possible Careers: This specialization may prepare you for roles such as:

• Project management specialist
• Information systems manager

O*NET OnLine describes project management specialists as analyzing and coordinating a project’s schedule, timeline, staffing and budget and leading the work of technical staff. It lists information systems manager as a reported job title for computer and information systems managers.

Prerequisites: Check whether the program expects work experience or technical skills related to data science, and whether it asks for a grounding in linear algebra, calculus and programming languages.

How to Choose a Data Science Specialization

A few checks can help you compare specializations across programs:

• Start with the work you want to do. Look at the roles listed under each specialization above. O*NET OnLine, sponsored by the U.S. Department of Labor, has occupation reports that describe each role’s typical tasks, skills and education, and our guide to data scientist skills covers the technical and soft skills many data roles share.
• Compare the math and programming each track assumes. Check the prerequisites a program lists for a track against the coursework you have already completed.
• Read the course list, not just the track name. Compare the required courses and electives in each track to see what you would actually study.
• Ask whether you must choose a track. If you are still deciding, check whether a program lets you build a focus through electives instead.

FAQs About Data Science Specializations

There are many nuances to the different types of data science specializations. Below, we provide answers to some frequently asked questions that may help make your decision process a little easier.