What Can You Do With a Master’s in Data Science?

Across industries, data has become essential to solving problems and making strategic choices. Whether predicting disease outbreaks, optimizing supply chains, or personalizing your Netflix recommendations, data provides the foundation for making informed decisions. As organizations rely more heavily on data, they need professionals who can turn complex information into measurable results. 

With companies such as Google, Amazon, and Pfizer investing billions of dollars in artificial intelligence (AI) and analytics, a career in data science can offer opportunities to work on high-impact projects in a wide range of fields. Earning an advanced degree can help you build the technical skills and professional competencies needed for roles in machine learning, business intelligence, data engineering, analytics, and more. Figuring out what you can do with a master’s in data science ultimately depends on your interests and career goals.

What Is a Master’s in Data Science?

Data science is the process of converting raw data into meaningful insights. It combines statistics, computer science, analytics, and industry-specific knowledge to help organizations identify patterns and make smarter strategic decisions. 

A Master of Science (MS) in Data Science can help students develop the technical and analytical skills to work with complex datasets. While curricula vary by program, students often study core areas such as: 

• Data gathering: Collecting structured and unstructured data to trace their origins  
• Data wrangling: Cleaning, organizing, and preparing data for analysis  
• Data analysis: Applying statistical and computational methods to uncover patterns and trends  
• Machine learning: Building algorithms that can make predictions and automate tasks  
• Data visualization: Turning insights into clear visuals that make data easier to understand  
• Big data technologies: Using technologies such as Apache Hadoop and Apache Spark to manage large datasets 

Many programs also introduce advanced topics that are shaping the field, such as deep learning, natural language processing, cloud computing, edge AI, and blockchain. These areas reflect the growing application of data science in technologies such as autonomous driving systems, virtual assistants, recommendation engines, and large-scale analytics platforms.

Key Skills Gained in an MS in Data Science Program

Excelling in a data science role requires more than the ability to work with numbers. Data scientists and other professionals often move between highly technical work and broader conversations about what their findings mean. They need to be comfortable not only analyzing and interpreting data but also explaining their insights clearly to others.  

Aspiring data scientists can benefit from developing the competencies below. 

Technical Skills  

Honing your technical skills and expertise can prepare you to work through the data science process, from preparing raw datasets to developing machine learning models. Common technical skills you can build in an MS in Data Science program include:  

• Programming languages: Using languages such as Python, R, SQL, and Java for data manipulation and analysis  
• Machine learning and AI: Applying supervised and unsupervised learning, deep learning, and neural networks to identify patterns and build predictive models  
• Big data technologies: Working with technologies such as Apache Hadoop, Apache Spark, and cloud-based data solutions to process and manage large datasets  
• Statistics and math: Applying probability, linear algebra, and statistical modeling to analyze data  
• Visualization: Using tools such as Tableau, Microsoft Power BI, and Matplotlib to present findings in easy-to-understand visual formats  
• Data cleaning: Preparing raw data for analysis 

Soft Skills  

In addition to technical expertise, data professionals need to understand the context behind the numbers and explain their analysis to other stakeholders. A master’s in data science program can also help you develop the following soft skills: 

• Problem-solving: Using data to investigate problems and identify practical solutions  
• Communication: Presenting findings clearly to nontechnical audiences  
• Business acumen: Understanding how data science can support business goals across various industries 
• Collaboration: Working with engineers, executives, analysts, and other professionals to turn data insights into action 

Careers With an MS in Data Science 

The career paths for a master’s in data science graduate can span roles in analytics, engineering, machine learning, and business intelligence, among others. Below are six roles commonly associated with the field.  

1. Data Scientist 

Data scientists closely analyze complex data to identify patterns and trends, gleaning insights that can support business decisions. Their work may involve developing machine learning models to automate business functions and creating predictive analytics to forecast future trends.  

Data scientists earned a median annual salary  of $112,590 in 2024, according to the U.S. Bureau of Labor Statistics (BLS).  

2. Data Engineer 

Data engineers design and maintain the infrastructure that organizations use to process and store data. They’re often responsible for creating and maintaining data pipelines and improving database performance to support more efficient business operations.  

Data engineers earned a median annual salary of about $99,900 as of April 2026, according to Payscale.  

3. Machine Learning Engineer 

Machine learning engineers use AI-powered models to power automation and prediction. Their work often involves training and refining algorithms and assisting in the development of deep learning models for AI applications. 

Machine learning engineers earned a median annual salary of about $125,000 as of April 2026, according to Payscale.   

4. Business Intelligence Analyst 

Business intelligence analysts help businesses improve their strategies by extracting actionable insights from raw data. They use various SQL and business intelligence tools to manage and analyze business data, and develop interactive reports and dashboards so that other stakeholders can access the information. 

Business intelligence analysts earned a median annual salary of about $80,000 as of April 2026, according to Payscale.  

5. Data Architect 

Data architects design and maintain the infrastructure that organizations use to store, manage, and access data. They’re also responsible for ensuring data security and compliance.  

Data architects earned a median annual salary of about $123,100 in 2024, according to the BLS. 

6. Data Analyst 

Data analysts interpret data and generate reports to support business decisions. Their work entails collecting and analyzing data from a variety of sources, and they may also assist with market research, including competitor analysis. 

Data analysts earned a median annual salary of about $70,400 as of April 2026, according to Payscale.    

Job Growth in Data Science     

As organizations increasingly rely on data to guide strategy and improve operations, data science is expected to remain a promising career path in the coming years. According to BLS projections, data scientists will be the fourth fastest-growing occupation in the country over the next decade, with employment growth of 34% between 2024 and 2034 — creating roughly 82,500 new jobs.  

That demand extends to several related career paths for master’s in data science graduates. The BLS projects 21% growth for operations research analysts, 7% growth for market research analysts, and 9% growth for management analysts, leading to hundreds of thousands of new jobs across these fields. 

Together, these projections suggest that developing data science skills can support several career trajectories, from building algorithmic models and managing data systems to analyzing business trends and helping organizations make more informed decisions.  

Unlock Data’s Hidden Power  

Earning a master’s in data science can prepare graduates to pursue roles that connect technical expertise with real-world decision-making. Schiller International University’s MS in Data Science program trains students to master Python, machine learning, and databases, helping them develop the skills to transform raw numbers into boardroom strategies.  

At Schiller, you’ll learn from industry veterans, collaborate on global projects, and join a network of more than 30,000 alumni.  

Are you ready to transform data into impact? Apply now! 

Recommended Readings 

What Makes a Postgraduate Student Different? (And Why Employers Notice) 

Is a Data Science Degree Worth It in 2026? 

Top Five Emerging AI Technologies Every International Student Should Know