Senior Data Analyst

Development and Alumni Relations (DAR) supports Johns Hopkins’
focus on research, teaching and patient care, and its role as a
national and global leader in higher education. We create and
foster enduring relationships that result in advocacy and
philanthropic support for Johns Hopkins University & Medicine;
strengthening the institution through partnerships with donors,
alumni, volunteer leaders, faculty, students, staff, and
patients.

Johns Hopkins University supports a flexible work
model that includes four different work modalities. This role has a
hybrid work arrangement with an onsite presence of 3 days per week.
The manager will confirm the team’s core onsite days where the
majority/all team members will work in the office. Employees who
travel on university business can count those days towards their
onsite days.
The Data Analyst at Johns Hopkins University reports
to the Director of Data Analytics and Giving Technology in the
Office of Annual Giving (OAG), and is a critical piece of data
management and reporting for the central Office of Annual Giving
team at Johns Hopkins.
The Data Analyst will exhibit excellent quantitative
and analytical capabilities, strong understanding of new and
emerging fundraising and quantitative modeling techniques and
technologies, have a background in database and Customer
Relationship Management (CRM) software and project management, and
the ability to convert complex data into engaging, informative
management reports.
The Office of Annual Giving is a growing team that
currently consists of twenty-two colleagues who provide annual
giving services to the nine schools of the university, various
departments of Johns Hopkins Medicine, and several centers and
institutes, totaling over 35 partners. These annual giving services
include developing comprehensive and integrated direct response
solicitation strategies that are optimal for each unit.
Reporting and Analysis
(50%)

• Provide strategic analysis of revenue and donor acquisition to
  assist with the creation and/or use of solicitation data, annual
  giving predictive models, dashboards, and trend analysis for
  development units.
• Provide strategic guidance to optimize the level of
  undergraduate participation.
• Working closely with OAG colleagues, provide development units
  on: annual giving strategies focused on data-driven approaches,
  domestic and international regulations regarding mass
  solicitations, and giving day/reunion best practices.
• Calculate, track, and report data to benchmarking studies
  including the Voluntary Support of Education (VSE), Blackbaud
  Target Analytics Undergraduate Giving Benchmarking report, and
  USWNR. Create and maintain standard operating procedures for a
  two-team validation process, including the Office of Advancement
  Services (OAS), and an archiving system of benchmarking data.
• Create and update annual giving dashboards for development
  offices, providing details on revenue, donors, appeal response
  rate, ROI, and spatial trends.

Data Engineering (30%)

• Using the institutions’ donor database, JHAS, and other data
  software including but not limited to: SQL, SOQL, Tableau, Power
  BI, Python, and Excel, establish annual metrics, reports, and
  dashboards for the development units, including the Homewood
  Undergraduate Program.
• Create automated processes to extract and manipulate data
  required for donor solicitations, ensuring a high level of data
  accuracy, usefulness, and reliability

Other (20%)

• Provide high-level project management for assigned unit data
  requests, ensuring reports are created and implemented in alignment
  of unit needs and goals.
• Create documentation to expand use of resources and ensure
  consistent and transparent policies and procedures across the OAG
  team.
• Offer assistance and mentorship to Data Analyst by sharing
  knowledge and providing shadowing opportunities.
• Other duties as assigned by the Director of Data Analytics and
  Giving Technology.

Minimum Qualifications

• Bachelor’s degree.

• Five years of related experience.

• Additional education (Master’s level) may substitute for
  required experience, to the extent permitted by the JHU equivalency
  formula.

Preferred Qualifications

• Master’s degree.
• At least five years of progressive experience in data analytics
  and data operations.
• Experience building data pipelines or designing ETL
  processes.
• Experience writing advanced SQL and/or SOQL queries.
• Familiarity with data warehousing and engineering concepts,
  including Extract-Transform-Load processes.
• Comfortable working in a complex, multi-divisional,
  fast-moving, results-oriented environment.
• Strong interpersonal skills with an ability to influence and
  drive consensus.
• Demonstrated success in project management while overseeing
  multiple priorities.
• Ability to establish priorities, set objectives, and achieve
  goals.
• Ability to organize and interpret complex data sets and utilize
  analytic techniques and platforms.
• Ability to identify multi-variables needed to optimize
  engagement and predictive indices.
• Strong written and verbal communication skills, including
  presentation capabilities. Experience presetting data to leadership
  team for decision-making purposes.
• Experience in using data visualization tools (i.e. Tableau,
  Power BI, or similar).
• Advanced knowledge of Excel, including experience with Power
  Query, VBA & Macros, Pivot Tables, and lookups.

All applicants are expected to uphold the university’s core
values which includes diversity and inclusion. All staff treat
people with dignity and respect by being fair and consistent. We
demonstrate an open-minded approach to understanding people
regardless of their race, gender, age, national origin, religion,
ethnicity, disability status or other characteristics. We show
respect for the beliefs and traditions of others; encourage and
promote practices that support cultural diversity; and discourage
behaviors or practices that may be perceived as unfair, biased, or
critical toward people with certain backgrounds.