What Can I Do with a Master’s in Data Science and Analytics?

Jobs in information technology are ranked in the "Best Jobs in America" by Money Magazine year after year. An article from The Economist explored which degrees give the best financial returns and another article from Forbes Magazine listed the majors with the highest starting salaries.

Students graduate from our programs with a solid education and get good jobs with outstanding employers such as Raytheon, PNC Bank, Minitab, DataForma, Remote Database Experts, and Future POS. Graduates can also be found in successful positions in local schools, banks and small businesses, as well as government positions.

1. Design, implement, populate, and query relational databases for operational data.
2. Design, modeling, data integration (ETL), analysis, querying, and reporting of data warehouses using analytical databases. Evaluate the use of data from acquisition through cleansing, warehousing, analytics, and visualization to the ultimate business decision.
3. Perform quantitative data analysis using appropriate statistical methods and tools (SAS) to aid business decisions and reduce the risks and optimize solutions.
4. Explore data to understand relationships among variables and harness/mine very large data sets to make business decisions using machine learning techniques.
5. Build and apply machine learning algorithm-based predictive models to make predictions for new data. Partition data to train, validate, and test the predictive models. Assess model performance for deploying the model offering the best predictive accuracy. Use ensemble models to improve predictions.
6. Apply data visualization best practices to communicate visual insights through charts, dashboards, and to communicate data-driven stories.
7. Discern when to implement relational versus non-relational database systems. Execute real-time analytical methods on streaming datasets to react quickly to customer need.
8. Integrate, apply, and implement the concepts, techniques and tools of data analytics learned  in the MS DSA Program using capstone projects with real-world datasets.
9. Identify and explain knowledge in data science, big data, and technology used for processing big data and data science methods.
10. Formulate and solve data science and big data problems using appropriate data management and analysis skills.
11. Identify and apply the technology necessary to aid in solving real-world problems.
12. Effectively use technology to solve data science problems.
13. Be literate in the language of data science and in data analysis skills for data science and big data.