Data Analyst vs Data Scientist

Data is everywhere. With the right tools and skills, you can use data to make predictions and solve complex problems. If you’re interested in working with data, you may want to consider becoming a data analyst or data scientist. Learn more about the differences between data scientist and data analyst career paths.


University of Cape Town


UCT Data Analysis

Learn how to sort, analyse, and interpret data to inform business strategy.

The London School of Economics and Political Science


Data Analysis for Management

Study data analytics with a world-leading social science university.

University of Cape Town


UCT Business Analytics

Learn how to apply data analysis techniques to make sense of number sets and drive better business decisions.


The program cards/tables featured on this page were last updated in April 2022. For the most current program information, please refer to the official website of the respective school.

The world is becoming increasingly reliant on data, and that’s a great sign for anyone interested in a data-driven career. According to the U.S. Bureau of Labor Statistics (BLS), some data occupations—including data scientists and analysts—are projected to grow by as much as 36% between 2021 and 2031. That’s much higher than the average for all occupations.

What Does a Data Analyst Do?

When a company wants to make sense of data—whether it’s been collected in-house or elsewhere—they often rely on data analysts to make sense of all the information. Data analysts may be responsible for cleaning and formatting data before identifying trends that can help business leaders make strategic decisions.

Conducting data analysis involves a variety of tools, skills and computing languages to perform statistical analyses and answer questions to solve organizational challenges. A data analyst may use a query language like SQL, programming language like R and SAS, and visualization tools like Power BI and Tableau in the course of their work. This often involves figuring out how to deal with missing data.

Strong communication skills are also useful in data analysis. Data analysts are often required to convey their findings to outside teams or stakeholders, explaining their reasoning and research to justify their conclusions.

What Does a Data Scientist Do?

Data scientists’ work is focused on creating the algorithms and predictive models that data analysts use to collect, sort, and analyze information. They help to develop tools and methods to extract information, create automation systems to eliminate routine work, and build data frameworks tailored to their organization.

While data scientists often perform different tasks from data analysts, these roles can overlap. As a more senior role, a data scientist often has a background in data analysis. This allows them to understand how analysts approach their work and build solutions that generate relevant insights.

Soft skills, such as business intuition, critical thinking and innovative problem solving, are also important in this advanced position. If you can stay one step ahead of your organization’s challenges, you can prove to be a highly valuable asset and stay competitive as a professional.

Differences and Similarities Between Data Analysts and Data Scientists

Data analysts and data scientists serve important yet distinct roles in an organization. Here are a few ways they can contribute to the same data set or project:

  • A data analyst makes sense out of existing data through routine analysis and writing reports. A data scientist works on new ways to capture, store, manipulate and analyze that data.
  • A data analyst works toward answering business-related questions. A data scientist works to develop new ways to ask and answer those questions.
  • A data analyst relies on database software, business intelligence programs and statistical software. A data scientist uses Python, Java and machine learning to manipulate and analyze data.

No matter which path you choose, keep in mind that both careers require at least a bachelor’s degree in a quantitative field, such as mathematics, computer science or statistics. If you love working with numbers and enjoy computer programming, becoming a data analyst or scientist will give you the opportunity to develop actionable insights for your organization.


Syracuse University


Master of Science in Business Analytics

Looking to become a data-savvy leader? Earn your online Master of Science in Business Analytics from Syracuse University.

  • As few as 18 months to complete 
  • No GRE required to apply

Maryville University


Master of Science in Data Analytics

Earn your Master of Science in Data Analytics online from Maryville University in as few as 12 months. Prepare to transform business intelligence into business insights.

  • Graduate in as few as 12 months
  • Learn from accomplished faculty who teach using real-world examples from today’s business headlines
  • Develop critical skills in leading technologies like R, Python and PowerBI
  • Grow your skills in computer science, statistics, data mining, data modeling, business intelligence, dashboards and visualization

Harvard University


Certificate in Business Analytics

Harvard’s 9-month certificate program equips high-level executives with the data and analytics skill set to lead their organizations to the industry forefront.

  • Live online classes in a webcam-enabled online classroom
  • Case-based lessons pioneered by Harvard Business School (HBS) faculty
  • In-person learning experiences at immersions hosted on Harvard Business School’s campus in Boston

University of Sydney


Master of Data Analytics

Learn how to use data analytics to empower your business with insights and drive informed decision-making. Earn a Master of Data Analytics online from the University of Sydney in 36 months part time.

  • Complete the course in 36 months part time
  • Study 100% online from anywhere
  • Four start dates per year


Data Analyst vs. Data Scientist: Education and Work Experience

Education: As mentioned above, becoming a data analyst or data scientist requires at least a bachelor’s degree in a quantitative field. However, some analysts may have a bachelor’s in business with an analytics focus. According to a report by O*NET OnLine, 76% of business intelligence analysts have a bachelor’s degree and 14% hold a master’s degree.

A 2023 Burtch Works study of salaries for data scientists and predictive analytics roles [PDF, 1 MB] revealed that 31% of professionals surveyed held a bachelor’s degree, 57% held a master’s degree and 12% had earned a doctoral degree. The study also found that professionals with advanced degrees earned higher salaries than those with a bachelor’s degree.

Work Experience: The Burtch Works study also noted that employers are placing a strong emphasis on hiring knowledgeable candidates who require little to no training. You may be able to gain relevant experience in a data science bootcamp or master’s program in data science.

Data Analyst vs. Data Scientist: Roles and Responsibilities

A data analyst or data scientist’s role and responsibilities can vary by industry and organization. It can be helpful to read through job descriptions to gain an understanding of what a particular company expects from its data professionals. As you do, keep in mind that many companies use the two positions interchangeably. This means that in some cases, job postings for data scientists will really involve typical data analyst skills and responsibilities, and vice versa.

Here are a few common job responsibilities for each role to help you determine whether an employer is looking for skills in data analytics or data science.

Data Analyst Responsibilities:

  • Data querying with SQL
  • Data analysis and forecasting with Excel
  • Creating dashboards with business intelligence software
  • Performing various types of analytics (descriptive, diagnostic, predictive or prescriptive)

Data Scientist Responsibilities:

  • Mining data with APIs or ETL pipelines
  • Cleaning data with programming languages such as Python and R
  • Performing statistical analysis
  • Creating programming and automation techniques to simplify day-to-day processes
  • Developing data infrastructures

Data Analyst vs. Data Scientist: Skill Comparison

To better understand how data analyst skills and data scientist skills compare, take a look at some of the more common tools and processes each role relies on.

Data Mining
Data Mining
Data Warehousing
Data Warehousing
Math, Statistics
Math, Statistics, Computer Science
Tableau and Data Visualization
Tableau and Data Visualization/Storytelling
Python, R, JAVA, Scala, SQL, Matlab, Pig
Business Intelligence
Big Data/Hadoop
Advanced Excel Skills
Machine Learning

Data Analyst vs. Data Scientist: Job Outlook

According to the BLS, data analysts can look forward to a 23% growth in demand, and data scientists can expect a projected 35% increase in demand from 2022 to 2032. This is much faster than the average for all occupations.


Syracuse University


Master of Science in Applied Data Science

Syracuse University’s online Master of Science in Data Science can be completed in as few as 18 months.

  • Complete in as little as 18 months
  • No GRE scores required to apply

University of California, Berkeley


Master of Information and Data Science

Earn your Master’s in Data Science online from UC Berkeley in as few as 12 months.

  • Complete in as few as 12 months
  • No GRE required

Southern Methodist University


Master of Science in Data Science

Earn your MS in Data Science at SMU, where you can specialize in Machine Learning or Business Analytics, and complete in as few as 20 months.

  • No GRE required.
  • Complete in as little as 20 months.


Data Analytics vs. Data Science: How the Two Careers Are Different

While data analysts and data scientists can work on the same teams and projects within an organization, their career paths are not necessarily the same. Explore the professional opportunities for both roles to help you determine the right option for you.

Career Growth

In an entry-level data analyst role, your main responsibilities will likely involve reporting and creating dashboards. From there, you might move on to a strategic or advanced analytics role, which can prepare you to manage a team after a few years in the field. Finally, you may continue your education and transition to a data scientist role.

As an entry-level data scientist, you may work with a team to conduct advanced research and analytics and gain relevant experience working with algorithms and statistical models. Depending on your goals, you may hone your leadership skills and become a data science manager. You may take your career even further and take on a director-level position or become a freelance data consultant.

Other Related Careers

For more information on careers in data science, check out these helpful guides:

Data Analyst vs. Data Scientist FAQ

Is data science or data analytics a better degree?

The best degree for you depends on your personal and professional goals. If you’re interested in data processing and statistical modeling, a degree in data analytics may be right for you. If you’re interested in machine learning or big data, you may want to pursue a degree in data science.

Can a data analyst become a data scientist?

There can be some overlap between data analyst and data scientist jobs, which may be helpful when transitioning between roles. One of the best ways to develop relevant skills and stay on top of your education is to keep learning and building experience.

What are common skills used by data analysts and data scientists?

Common skills used by both data analysts and data scientists may include data mining, data warehousing, math, statistics and data visualization. Depending on their role in an organization, some data analysts may use programming languages such as R or Python.

What is the salary difference between a data scientist and a data analyst?

According to O*NET OnLine, data scientists earned a median salary of $103,500 in 2022. The BLS reported a median salary of $85,720 for data analysts in 2022.

Last updated: October 2023