Data Strategy Analyst, Brandeis Career Center
$59,400–$78,500 year
HybridBrandeis, California, United States
Job Summary
Develop and manage the Career Center's comprehensive data strategy, establishing governance practices, standardized definitions, and reporting protocols to ensure data integrity across undergraduate and graduate populations. Lead analysis of student engagement, career outcomes, and program data to generate actionable insights for strategic decision-making, while owning the full lifecycle of the First Destination Survey including methodology, design, and reporting. Create dashboards and visualizations to communicate findings to leadership and external stakeholders, integrate multiple data sources including CRM systems and survey platforms, and support advanced analytics such as predictive modeling and applied AI. Partner with Institutional Research and academic units to strengthen assessment plans, align data architecture, and train staff on data literacy. Work 35 hours per week on a hybrid schedule with occasional weekend requirements.
Required Qualifications
- Bachelor's degree
- 3–5 years of experience in data analytics, reporting, or data management
- Strong analytical skills with the ability to interpret complex data and communicate insights clearly to diverse audiences
- Advanced proficiency in Excel
- Experience with data visualization tools (e.g., Power BI, Tableau)
- Demonstrated experience developing dashboards and reports for decision-making
- Experience working with multiple data systems and integrating data from various sources
- Strong collaboration and communication skills, with the ability to work across teams and functions
- Occasional early morning, evening, or weekend work may be required
Desired Qualifications
- Degree in data analytics, statistics, data science, or a related field
- Experience with survey tools and statistical software (e.g., Qualtrics, R, SPSS, SAS, or similar)
- Strong understanding of data visualization best practices and user-centered reporting design
- Experience with predictive modeling, forecasting, or applied AI in a professional setting
- Experience working with enterprise data platforms or cloud-based analytics environments
- Knowledge of FERPA and data privacy standards in higher education
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