At National University, we believe it’s not just about the degrees our students earn, but the degree to which they use them.

Since 1971, we have supported working professionals who want to be a powerful force for positive change. That’s why we make education accessible to adults who live and work in the real world. It’s why we were the first to develop a flexible, one-class-per-month format. It’s why we offer more than 120 graduate and undergraduate degree programs. And it’s why we will continue to innovate and leave a mark on people who will one day leave their mark on the world.

We embrace diversity. Because it brings a new perspective to every industry. Our classes and faculty are made up of an eclectic mix of people who reflect our different communities and have the influence to shape where we’re headed.

We do all this because we care. About our students. Our staff. Our supporters and our community. We are a private, nonprofit institution that does not answer to shareholders. We invest our money back into making improvements so that the people who come here can do the same.

We know our legacy does not end when our students graduate. It begins.

As a Data Analyst on the Data Operations team, you will work cross-functionally with data engineers, data scientists, business experts, and external vendors to help National University deliver a better student experience by using data and analytics. You will work on a variety of projects that include building analytical models, coding, data visualizations, and storytelling to help us identify opportunities for our students, for our faculty and our staff. You will quickly become an expert in one of our key business and data domains (i.e., Learning, finance, financial aid, etc.) and work cross functionally in an analytics center of excellence to improve existing processes or analytical approaches.

The successful candidate will turn data into information, information into insight and insight into business decisions. Data analyst responsibilities include conducting full lifecycle analysis to include requirements, activities, and design. Data analysts will develop analysis and reporting capabilities. They will monitor performance and quality control plans to identify improvements.

Essential Functions:

• Interpret data, analyze results using statistical techniques and provide ongoing reports
• Develop and implement databases, data collection systems, data analytics and other strategies that optimize statistical efficiency and quality
• Acquire data from primary or secondary data sources and maintain databases/data systems
• Identify, analyze, and interpret trends or patterns in complex data sets
• Utilizes various software applications and reporting tools to deliver actionable data to end-users in an understandable format
• Build sophisticated data pipelines using SQL, Python, and internal workflow management tools to provide visibility to operational process
• End-to-End manage data warehouse and reporting pipeline build
• Manage stakeholder expectations and project manage design, development and delivery of data solutions, own data analysis where needed, and communicate the outcomes/insights to various collaborators to aid strategic decisions for improvements
• Filter and “clean” data by reviewing computer reports, printouts, and performance indicators to locate and correct code problems
• Work with management to prioritize business and information needs
• Locate and define new process improvement opportunities

Education & Experience:

• A Bachelor’s degree; preferably in Data Science, Computer Science, Statistics, Engineering, or other quantitative fields.
• 2 Years of experience in data analytics. Master’s degree in data analytics in lieu of experience.
• Knowledge of statistics and experience using statistical packages for analyzing datasets (Excel, SPSS, SAS etc.)
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy
• Adept at queries, report writing and presenting findings
• A demonstrated ability to query and extract findings from large data sets in relational databases such as SQL Server, Teradata, Oracle, etc.
• Experience with programming/scripting languages like R or Python
• Experience with advanced data visualization platforms such as Tableau

Competencies/Technical/Functional Skills:

• Quick on feet; willingness to discover alternative solutions to technical problems.
• A desire to solve complex problems with creative and concise solutions.
• Excellent written and oral presentation skills – ability to communicate findings with non-technical stakeholders in concise and simple terms.
• An individual who thrives in a collaborative environment.