Innovation propels business, but big data underpins innovation. From tech giants and mega-corporations to nonprofits and small businesses, harnessing the power of data and developing sophisticated methods to manage and analyze that data is a distinctive advantage that drives growth, efficiency, and profitability.

The field of data science is relatively new, so there are fewer degreed professionals than demand requires. This lowers the barrier to entry for professionals with non-computational backgrounds to attain degrees and enter the field. In addition, because the amount of data companies gather is constantly increasing, they face large challenges in organizing that data and extracting valuable insights. Read on to better understand all the data science career path opportunities open to you with an online Master of Data Science degree from Rice.

Rising Demand for Careers in Data Science

The field of data science is blossoming, with companies focusing on big data and digitization efforts as a way to use data for better outcomes and enhanced competitive success. Data is a valuable resource and companies across all sectors need skilled data scientists to efficiently organize and manage it and extract meaningful trends and patterns. As businesses worldwide ramp up their data collection efforts, the demand to fill different types of data science jobs will continue to grow, making the data science job outlook very positive.

Data scientists are valued members of organizations that identify opportunities to improve everyday life, ensure the safety of communities, preserve the environment, advance sustainable agriculture, empower the developing world and more.

Types of Jobs in the Field of Data Science

The field of data science offers versatile career paths for professionals who are skilled in managing complex data and mining specific insight from that data to answer complex problems. Career options in data science include:

Data Engineer

The world relies on data engineers to develop the systems and architectures that can transform data into useful information to solve specific problems. With a background in software engineering and programming, data engineers work with data science teams to customize and manage data integration tools, databases, warehouses, and analytical systems.

Database Developers

As organizations collect data, they need a place to store it. Database developers design, construct, program, and maintain databases for efficiency and performance.

Data Architect

Data architects work with data engineers to build a data management framework that centralizes, protects, and maintains data. The data architect is responsible for creating the plan or blueprint that the data engineer will use to build the enterprise data management framework.

Business Intelligence Developer

Business intelligence developers help to simplify complex information extracted from data. They can work with different types of data and use business intelligence software tools to improve the data research process and share the information extracted from data.

Machine Learning Engineers

Machine learning engineers use their programming and data modeling skills to design self-running software that automates predictive models, which control computers and robots. Data science teams use these systems to derive meaningful information from data.

Statistician

A data science statistician uses mathematical skills to interpret quantitative data in order to answer specific questions. Statisticians test and create data sampling techniques, experimental designs, and analytical methods.

Job Outlook for Data Scientists

Data scientists work within all industries and they are in demand for a number of reasons. First, businesses are focused on improving their data analytic capabilities and leveraging the cloud infrastructure. In addition, the amount of data that enterprises collect and store is growing exponentially. This means that business leaders will need to work more closely with data scientists, which leads to data science career growth opportunities.

Successful data scientists like exploring new ways to approach problems and discover new perspectives. They are organized and possess an acute attention to detail. They typically have experience in business management and are effective communicators who are able to work collaboratively. In addition, they have a desire to continue learning. As technologies evolve, it is important that data scientists continue to master new systems and processes.

Pursuing an advanced degree in data science from Rice University will prepare you for the rigors of a career in data science and the many different types of data science jobs. You’ll acquire the technical competencies necessary for success in the field, including the computational and statistical foundations of data science and technology management. You’ll learn how to apply your knowledge in different ways to solve problems and implement solutions like machine learning and artificial intelligence. You’ll produce relevant work that will demonstrate your capabilities to employers.

Take the Next Step in your Data Science Career

Applying for the online Master of Data Science program is streamlined. We offer three start dates per year and are committed to delivering a superior data science education in a flexible format. Learn more about the program and apply online today!