From Stanford University's posting. “We” and “our” refer to the employer.
Perform analytical data studies associated with strategic planning and decision-making covering a variety of policies, projects, programs, issues, or operations in support of a function, program and/or organizational unit, or in research of new or changing systems, programs, and audiences. May be involved with compliance with informational requests from external agencies.
Stanford Job Title:
Organizational Insight Analyst 1
VPUE Unit:
The Haas Center for Public Service
Job Code:
4748
Location:
Stanford Main Campus, Hybrid, 3 days on-site
Exemption Status:
Exempt, 2-year fixed-term
Budgeted Salary:
$140,000-145,000
The Office of the Vice Provost for Undergraduate Education and Haas Center for Public Service are seeking an Assessment and Program Evaluation Analyst to lead and contribute to all phases of mixed-methods evaluation projects and build evaluation infrastructure for the Haas Center. The analyst will report to VPUE’s Senior Director of Evaluation and work closely with members of the VPUE Assessment and Program Evaluation (A&PE) team and Haas Center staff. This is a fixed-term, two-year position without expectation of renewal.
There are three major areas of evaluation project support needed by the Haas Center.
Evaluation studies of Haas Center programs:
Conduct all phases of complex-mixed methods evaluations, from study design to dissemination of results, to inform continuous improvement of programs.
Analysis and reporting on center-wide application and participation data.
VPUE’s A&PE team and IT Department have collaborated to make Haas center application and participation data accessible to staff via an interactive dashboard that is in need of feature enhancements and maintenance.
Build a coherent infrastructure for evaluation across Haas programs.
Drawing on the activities in 1 and 2 above, create resources that support continuous improvement across the Haas Center, such as shared survey question banks that programs can draw from.
Together, Haas Center staff and leadership have articulated the Haas Student Learning Outcomes Framework that identifies center-wide expected outcomes for students and will inform all Haas program evaluation work. Existing records, such as application and participation data, written student reflections, and student survey responses, are available to inform the work. New data collection will also be needed for some studies.
Across all areas, the analyst will lead and contribute to the following activities:
Evaluation design.
Develop evaluation designs, including data collection instruments and analysis plans.
Collect input from Haas-affiliated faculty and staff, VPUE’s Assessment and Program Evaluation team, and others.
Identify evaluation questions that are likely to yield actionable findings and align with Haas program needs and the center as a whole.
Prioritize approaches that can be used in multiple programs and sustained beyond the two-year term position.
Conduct literature searches to identify data collection instruments aligned with evaluation goals.
Data collection and management.
Collect new program data and prepare existing data for analysis.
Use a variety of data collection approaches such as interviews, surveys, and focus groups.
Retrieve data such as participation records, program applications, and student written reflections from several secure data systems.
Store evaluation data securely following data use policies.
Analysis and reporting.
Analyze and synthesize data from a variety of qualitative and quantitative sources.
Create and present reports, data visualizations, and slide decks to inform Haas leadership.
Implement quarterly reporting processes for sharing regularly updated data with Haas leaders and other decision-makers.
Maintain and enhance data dashboards, verifying that data from multiple systems is successfully connected, complete, and up to date.
Create cross-program documentation of evaluation data and analysis approaches organized according to the outcomes framework.
In addition to the minimum requirements listed below, an advanced degree in a relevant field (such as social science, psychology, statistics, or similar) is preferred.
To be considered, please submit a cover letter and resume along with your online application. Your one-page cover letter should briefly describe your interest in the position and how your background and experience prepare you for success in the role.
Completed applications will be reviewed on a rolling basis beginning October 19, 2026.
Responsibilities
Core Duties: Answer questions by developing research methodology, gathering data and/or using appropriate statistical techniques on available data.
Drive the collection of new data and the refinement of existing data sources through the use of algorithms and/or other advanced techniques.
Fully analyze the problem, question existing processes and assumptions, gather data and information, find, and evaluate alternative solutions, and propose best course of action.
Explore data from multiple angles, determine meaning behind the data, and recommend ways to apply the data.
Communicate, convey, and visualize informed conclusions and recommendations across an organization’s leadership structure in a manner that “tells the story” behind the data and influences how the organization approaches the challenge.
May interact with senior leaders and faculty with written summaries and/or presentations on assigned research.
May delineate the information to be gathered, collect data at the project inception, prescribe how to structure the data, and specify the data warehousing structure for future access.
Through data, may predict what actions will be taken in a designated timeframe for a prescribed issue/challenge.
May need to collaborate with other organizations to gather data.
Proactively seek and locate data, including outside benchmarks or comparative data, to support or refute proposed decisions.
Minimum Education: Bachelor’s degree.
Minimum Experience: Four years extensive experience or combination of education and relevant technical field experience solving analytical problems using quantitative approaches.
Knowledge, Skills and Abilities: Demonstrated experience querying, processing, analyzing, and reporting on large data sets.
Proficiency in manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources.
Experience in empirical research and answering hard questions with data.
Interpersonal and communication skills to effectively convey findings and influence senior leadership & faculty.
Ability to use data retrieval and manipulation tools such as SQL, R, Python, etc. in conjunction with data visualization tools such as Tableau to present data clearly to non-technical audiences.
Familiarity and experience with intermediate statistical methods; advanced proficiency with statistical tools such as SPSS, STATA, R or similar tools.
Ability to tell stories with data using data visualization software Ability to present data clearly to non-technical audiences.
Flexible analytical approach allowing for results at varying levels of precision.
Familiarity with strategic planning concepts.
Strong project management skills.
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