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Job ID: 129933

Senior Data Systems Analyst (0599U) - 1668
University of California, Berkeley


Date Posted Sep. 27, 2019
Title Senior Data Systems Analyst (0599U) - 1668
University University of California, Berkeley
Berkeley, CA, United States
Department N/A
Application Deadline Open until filled
Position Start Date Available immediately
 
 
  • Professional Staff
  • Alumni Relations
    Communications/Public Relations
    Information Technology
 
 

University Development and Alumni Relations (UDAR) increases support for and enhances knowledge of UC Berkeley through communications, public outreach, and fundraising. The department is responsible for centralized fundraising and donor engagement, and works to strengthen unit development offices by consulting and partnering with campus fundraisers. University Development and Alumni Relations also handles a range of central activities and services encompassing events, communications, stewardship, prospect development, gift management, database management, and more.

Advancement Information Services (AIS), a unit within UDAR, develops and delivers the primary business data and systems that support the work of University of California, Berkeley’s centralized and decentralized fundraising activities. AIS oversees several interrelated information technology systems and tools, including the Cal Advancement Data System (CADS), the database in which advancement professionals research and record fundraising activity. AIS encompasses five units: Advancement Data Quality and Management, Information Technology, Planning and Analysis, Information Strategy and Analytics, and Helpdesk.

Job Summary

This Senior Data Systems Analyst is a member of the Information Strategy and Analytics team. This group provides a broad set of information delivery and analytic tools and services to help fundraising teams across campus operate as data driven programs. As the University embarks on its most ambitious fundraising campaign ever, information delivery and analysis will be one of the most important components of our shared success over the next several years.

The successful candidate applies expert level knowledge of data management and data analysis to support the strategic planning and operational effectiveness of key advancement programs, including annual, major, principal, and planned giving; donor engagement and stewardship; volunteer identification and recruitment; and alumni relations. It involves gathering, managing, and evaluating internal and external data using data preparation, predictive modeling, forecasting, and statistical analysis techniques to help identify, classify, understand, engage, and steward constituents of the University. It includes planning, designing, developing, implementing and administering databases to acquire, store, and retrieve data; developing solutions to improve information flow and architecture; and implementing new tools and applications to meet requestors’ business requirements; validating requirements against needs. Ensures accuracy and completeness of data; establishes and maintains data security. Develops and maintains database dictionaries, tables and data elements.

Responsibilities

Apply statistical hypothesis testing methods to estimate the impact of decisions and quantify the uncertainty surrounding decision making.
Communicate findings to members of the advancement community.
Assist with efforts to promote the use of data-driven decision-making within campus advancement community.
Collaborate with University of California, Berkeley schools, colleges, and units to identify and deliver sophisticated analysis products and analytics-based solutions for growing fundraising opportunities and improving fundraising processes.
Schedules and conducts analysis sessions.
Synthesize information and disseminate results by producing informative reports, tables, presentations, and visualizations (e.g., charts, maps, and infographics).
Continuously improve the quality of available data and reproductibility of analyses by developing and contributing to standard processes.
Prepare reusable standard analysis procedures and specifications to access data warehouses, import and/or move data between stores, and take random samples.
Maintain data dictionaries to support knowledge transfer.
Uses internal and external data sources and advanced statistical modeling and data mining techniques to identify overall trends and patterns in giving, volunteerism, event participation, etc. and search for explanations and underlying causes.
Develop predictive models for decision support and forecasting revenue.
Gather relevant internal data sources and supplement with external sources (e.g., census records, surveys, social media, market research) to develop useful data models for analysis.
Collaborate with data management groups to identify, improve, maintain, and share data from the University’s various internal sources.
Identify internal and external sources of collaboration and benchmarking.
Stay abreast on trends in fundraising and market analysis.

Required Qualifications

Requires advanced knowledge of data management systems, data administration practices and standards.
Must have advanced knowledge relating to logical data design, data warehouse design, and data integration as well as the management of web content or other unstructured data.
Must be able to prepare complex data models unassisted.
Must be able to prepare important types of data models, such as logical/relational models, dimensional models and document models.
Should be familiar with data model patterns in several common business or academic domains.
Should be able to understand and model complex knowledge-intensive processes such as scholarly and research processes.
Must be experienced in logical data design, data integration and the specification of data services.
Should be knowledgeable about data quality and governance issues and requirements.
Strong analytical and design skills, including the ability to abstract information requirements from real-world processes to understand information flows in computer systems.
Ability to represent relevant information in abstract models.
Proven modeling and information design skills.
Critical thinking skills and attention to detail.
Excellent interviewing and listening skills.
Good negotiation and influencing skills.
Very good written and oral communication skills. Education/Training:

Bachelor’s degree in related area and/or equivalent experience/training.

Preferred Qualifications

Advanced Tableau Skills preferred.

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