How a Computer Science Master’s Can Prepare You for Data Scientist Jobs

Data science is a hot field. U.S. News and World Report ranks data scientists fourth among its best technology jobs, seventh among its best STEM jobs, and eighth in its overall 100 best jobs category (rankings are based on salary, position challenges, talent and skill requirements, stress level, advancement opportunities, and work-life balance).

There is substantial demand for data scientists across businesses and institutions. The U.S. Bureau of Labor Statistics predicts the data science job market will grow 35% from 2022 to 2032, making it the third-fastest-growing occupation in the nation. 

It’s no mystery what’s driving the data science boom. In a word: data. The amount of data available for analysis is increasing exponentially, a trend likely to continue as institutions implement more—and more granular—data collection practices. As global data generation grows and storage capabilities expand, organizations need more data scientists to analyze the information to drive informed decisions about strategies, processes, and projects.

For those interested in entering this rewarding and expanding field, earning a master’s degree in computer science, like the online MS in Computer Science (MSCS) from Case Western Reserve University (CWRU), offers excellent preparation. This article explores the role of a data scientist and discusses how an MSCS equips you with the skills for this in-demand field.

Career Overview: What is a Data Scientist and Why is Demand So High?

Information generation reaches new highs every day. Consider these numbers:

• The world generates over 2,500,000,000,000,000,000 bytes of digital data daily 
• Since 2010, the amount of digital data has grown continuously, with 90% created in the last two years

Businesses need data scientists to collect, organize, analyze and interpret this data and to develop new methods and products to accomplish these tasks. They employ math, statistics, artificial intelligence (AI) and computer science skills to process and analyze large quantities of information. Professionals undertaking this work may have titles such as financial analysts, statisticians, operations research analysts or software developers.

Strategic, accurate data evaluation can improve profitability, streamline processes and accelerate operations for a wide variety of industries, including:

• Healthcare and medicine: In the United States, big data analytics in healthcare has the potential to save $300 billion annually
• Finance and banking: Globally, the market for big data in this field should reach $14.83 billion by 2026, with a compound annual growth rate of 18.8% from 2019 to 2026
• Manufacturing and supply chain: Data-informed decisions can improve supply chain management by reducing holding costs by 20% and increasing fulfillment rates by 7%
• Retail and e-commerce: By using data science to personalize customer experiences, e-commerce companies can increase revenue by 6%
• Marketing and advertising: 69% of marketers view data-informed decisions as necessary to remain competitive.

Data scientists can harness the power of data and drive fact-based decisions. Industries recognize the need for skilled technicians in this field; the demand for data scientists rose 56% between 2020 and 2022. 

A Career-Focused Curriculum: Benefits of Earning an MS in Computer Science 

Data science requires highly developed skills and expertise. Research indicates that more than half of all employers seeking data scientists require candidates to have a master’s degree or PhD. The benefits of earning an MS in Computer Science from CWRU include:

• Advanced training in the latest technological advances
• Expertise development in four key areas: AI, databases and data mining, security and privacy, and software engineering
• Data-driven leadership skills
• Strong collaboration and teamwork mindset 

CWRU’s online MSCS curriculum keeps pace with this rapidly developing field, offering two tracks based on students’ technical experience. Both options provide a robust curriculum that builds the skills students need to meet current and future challenges of this innovative and technical profession.

Database Management Courses

Data scientists must ensure that databases are clean and organized. Database management systems (DBMS) assist with this by creating structured collections of data housed in tables with defined relationships. 

DBMS software (such as the popular SQL system) creates, manages and queries databases. Having insight into how these databases function is essential for data scientists, who leverage that information to better structure their data for analysis.

In Case Western Reserve’s online MSCS, the curriculum includes a “Database Systems” to study database systems, including organization, design, query languages, SQL and security.

Data Mining Courses

Data scientists must understand data mining tools, which analyze large batches of raw data to identify patterns. After collecting, storing and organizing the information, data mining uses algorithms and other techniques to sort and analyze the information. The trends identified through this operation help inform business decisions.

Popular data mining techniques include association rules, classification, clustering, decision trees, K-Nearest Neighbor, neural networks and predictive analysis. The rise of machine learning algorithms and AI has automated the mining of large data sets, such as customer databases, transaction records from web servers, mobile apps and sensors. This enables data scientists to evaluate larger amounts of data more efficiently than ever before. 

Case Western Reserve’s “Data Mining” course provides a strong foundation for managing and analyzing big data. In preparation for their careers, students learn about data warehouse and OLAP technology, data preprocessing, data mining primitives, languages, system architectures, mining association rules, classification and prediction, cluster analysis and mining complex data types.

Data Privacy Courses

As consumers increasingly share personal information with organizations, concerns about data security intensify. In fact, 9 out of 10 Americans consider online privacy essential.

Data scientists must preserve data privacy, which affects how sensitive data gets collected, analyzed and stored. Computer science students at CWRU learn how to execute these responsibilities in their data protection and privacy courses. “Data Privacy” covers crypto-based solutions for privacy, hiding data from the database user, anonymous routing and TOR, privacy in online social networks, cellular and Wi-Fi networks, location privacy and genomic privacy. In “Smartphone Security,” students explore Android programming and build comprehensive knowledge of mobile security, including permission, malware and UI analysis.

Data Structures and Algorithm Courses

Data scientists must understand data structures and algorithms, as these tools help data scientists manage large quantities of data effectively. 

• Data structures—e.g., arrays, linked lists, trees, stacks, queues and graphs—store and organize data in ways that make processing and retrieval more efficient 
• Algorithms—e.g., sorting, searching, hashing and graph algorithms—use systematic step-by-step procedures to solve problems

These two elements work together to store and retrieve data efficiently, manipulate information and develop solutions to solve problems. Mastering these skills enables data scientists to:

• Identify the appropriate data structure or algorithm to solve a problem
• Create programs that run more efficiently
• Evaluate complex problems and solve them systematically

At CWRU, “Analysis of Algorithms” exposes students to algorithm design and analysis through discussions about amortized analysis, NP-completeness and reductions, dynamic programming, advanced graph algorithms, string algorithms, geometric algorithms and local search heuristics. “High Performance Data and Computing” (HPDC) offers a hands-on exploration of the theoretical and practical aspects of HPDC. Theoretical concepts include computer architecture, parallel programming, HADOOP, general purpose GPU computing and performance optimization. Practical considerations include HPDC architecture, job scheduling/management and Linux scripting.

Artificial Intelligence Courses

Artificial intelligence and machine learning are pivotal in data science. The powerful benefits of AI in the DS profession include:

• Speed: AI delivers insights more quickly and accurately than humans can
• Fact-checking: AI tools detect and flag errors, finding potential problems before they occur
• Data democratization: AI helps make data more accessible to all
• Report generation: AI can create reports, ensuring all stakeholders receive information promptly

In “Introduction to Artificial Intelligence,” computer science master’s students explore the core concepts of intelligent systems, which include problem-solving with search, constraint satisfaction, adversarial games, knowledge representation and reasoning using propositional and first-order logic, reasoning under uncertainty, introduction to machine learning, automated planning, reinforcement learning and natural language processing.

Build Your Data Science Expertise with an MS in Computer Science from Case Western Reserve Online

Demand for data scientists will likely exceed supply by over 50% by 2026. Set yourself up for professional success with a degree that builds the expertise today’s employers want. Earn your MSCS online from Case Western Reserve. Connect with an enrollment adviser to learn more or start your application today.