brandeis
Data Strategy Analyst, Brandeis Career Center
At a Glance
- Location
- Brandeis - Waltham Campus, United States
- Employment
- Full time
- Experience
- 3–5 years
- Compensation
- Hiring Range: $59,400 - $78,500 Lead Career Center Data Strat
- Posted
- 2026-07-21
Key Requirements
Required Skills
Domain Knowledge
- Education
Benefits & Perks
ive and competitive benefits package designed to support your health, financ
Requirements
3–5 years of experience in data analytics, reporting, or data management
Advanced proficiency in Excel and 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
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
Compensation & Benefits
As the Data Strategy Analyst, you'll play a key role in helping the Brandeis Career Center measure and communicate its impact across undergraduate and graduate programs. Your work will shape strategy, inform institutional decision making, and ensure the Career Center uses data to continually improve programs, services, and student outcomes.
Join a growing, forward-thinking career center during an exciting period of transformation
Lead data strategy and analytics that directly influence organizational priorities and decision making
Partner with colleagues across the university and explore innovative approaches to analytics, data visualization, AI, and assessment to improve student success
Work on a collaborative team that values curiosity, continuous learning, innovation, and evidence-based decision making
Work Environment:
Responsibilities
Data Strategy and Governance (30%)
Develop and manage a comprehensive data strategy for the career center across undergraduate and graduate populations
Establish and maintain data governance practices, including standardized definitions, processes, and reporting protocols
Ensure data integrity, quality, and consistency across all systems and platforms
Oversee integration of multiple data sources, including CRM systems, survey platforms, and external datasets