The Business Applications unit within University Relations seeks a senior data analyst to join its team of data analysts and application developers. The senior data analyst will work to support advancement operations for the University of Maryland, which includes development (fundraising), alumni and donor relations, gift processing, and other functions. The senior data analyst will play a key role in enabling advancement business users to make data-informed decisions that will help the university reach its capital campaign goals to advance the University of Maryland strategic objectives.
 

The senior data analyst will manipulate and analyze advancement datasets to reach meaningful data driven conclusions and discoveries. They will work closely with business stakeholders to understand their goals and data dependencies, translate user analytics, and apply standard data analysis processes that conclude with sharing findings in written and presentable formats.
 

The data analyst maintains a sharpened kit of Business Intelligence (BI) tools and techniques to maximize enterprise value for end users. They have hands-on experience with various BI operations, including dashboards, visualizations, reporting, data mining and ETL, and are able to utilize these tools to improve data enablement for end users and to tell compelling data stories.
 

Finally, the senior data analyst works to support daily data needs in collaboration with other team members to efficiently complete incoming service requests while working closely to support Business Application data preparation, full stack development, data integration pipelines, and management of data and records.

Education (include licenses, certifications, etc.):

Bachelor’s degree required.

Experience:

• Candidates must have at least 7 years of overall Business Intelligence experience. 
• 3 years minimum experience in Python for data analysis, wrangling and/or mining. 
• Experience working in relational databases.

Knowledge, Skills, and Abilities:

• Working experience with Business Intelligence operations and tools (data mining, reporting, ETL and Visualizations)
• Proven experience in data analysis to extract meaningful insights and visually present them.
• Working knowledge of one or more of python’s data analysis libraries, such as Pandas, NumPy, SciPy, Seaborn, SciKit, etc.
• Excellent communication skills with the ability to prepare solid presentations, facilitate meetings, and summarize data findings for end users.
• Solid understanding of statistics and data analysis processes.
• Critical and creative thinking to know what to ask, to examine assumptions and support your conclusions with communicable/written findings.