Data Solutions Analyst

Position Summary:
The Data Solutions Analyst will serve as part of the Office of Data & Strategic Analytics (DSA) at Vanderbilt University working to address the data needs of Vanderbilt University’s Development and Alumni Relations (DAR) department. The Data Solutions Analyst will collaborate with Development and Alumni Relations to answer key strategic questions, such as:
-    How should Development and Alumni Relations focus its resources to maximize fundraiser effectiveness?
-    How can Development and Alumni Relations better utilize internal and external data sources to better identify prospects for fundraising initiatives?
-    How can Development and Alumni Relations improve alumni engagement, and how can we reliably measure and score that engagement?

The Data Solutions Analyst will be responsible for thinking critically and creatively to tell stories with data and deliver actionable insights to maximize performance of the Vanderbilt University’s development and alumni engagement efforts. The Data Solutions Analyst will be integral to building out a data driven culture within the Development Office and ensuring the future success of the department. This position will report to the Director of Data Analytics for Development & Alumni Relations.

The Data Solutions Analyst will be responsible for assisting the Director of Data Analytics in connecting and utilizing university data sources to identify new opportunities for donor engagement as well as developing tools to both improve effectiveness and measure success of development and alumni engagement efforts. They will work with internal stakeholders to develop strategies to optimize programs and investments that drive donor and alumni engagement. The position will serve a crucial role in certifying that appropriate connections are established for DAR-related efforts that will result in positive university-wide impact.

Applicants should be highly proficient in utilizing Business Intelligence (BI) tools and knowledgeable of university data; performing assigned activities such as defining data requirements, designing data models, building dashboards, developing BI reports, performing ad-hoc analysis, and writing SQL code to assist consumers in achieving operational and strategic goals. This position may also employ predictive modeling and analytics techniques to aid decision making in areas of strategic interest to the university administration.

About the Work Unit:
Vanderbilt University is a dynamic institution, pushing new ideas into the frontiers of discovery, challenging the limits of what is possible and working diligently in the service of others. To help make this possible, the Chief Data Officer and DSA are based in the Chancellor’s Office and work collaboratively with decision-makers and stakeholders across the university, supporting the strategic use of data. DSA comprises four teams: Academic Partnering, Administrative Partnering, Institutional Research and Assessment, and Data Governance, Solutions, and Consulting. DSA also works closely with data leaders in other parts of the university as well as with Information Technology teams.

The Data Solutions Analyst is part of the Administrative Partnering team and will work exclusively with the university’s Development & Alumni Relations team.

Key Functions and Expected Performance:

Business Intelligence Tools: Uses BI tools such as Tableau, and SQL (Oracle and Snowflake) to provide complex reporting solutions to meet consumer data needs.
•    Develop new analytics solutions; support and maintain existing solutions
•    Perform testing and evaluation of new BI analysis and reporting solutions, tool upgrades, enhancements and change requests
•    Identify existing solutions or design new solutions that satisfy information requests
•    Develop and maintain database tables for use in reporting
•    Recommend standardized practices in developing data solutions
•    Explore new techniques and technologies in BI to generate new ideas and insightful analytics
•    Support other team members through organized training and on-going knowledge transfer

Data Analysis: 
•    Analyze complex, broad data sets to develop actionable insights that can inform DAR strategy and drive development and alumni engagement efforts
•    Gather and clarify requirements to ensure that analytical outputs meet the needs of stakeholders
•    Develop new predictive models, using data from multiple sources, to better refine donor capacity and affinity while identifying new opportunities for donor engagement and increasing the effectiveness of fundraising teams
•    Understand and prepare raw data, apply data models using statistical methods and algorithms, and then extract and communica