Key Responsibilities and Required Skills for a Vocational School Analyst

🎯 Role Definition

A Vocational School Analyst is the data-driven storyteller and strategic partner for a career and technical education institution. This role is at the heart of our mission, translating complex data from student enrollment, academic performance, and post-graduation employment into actionable insights. You're not just crunching numbers; you're shaping the future of our programs and ensuring our students are equipped for successful, in-demand careers. This position bridges the gap between raw data and informed decision-making, directly impacting curriculum development, student support services, and the school's overall strategic direction.

📈 Career Progression

Typical Career Path

Entry Point From:

Data Analyst (in another sector)
Institutional Research Assistant
Educator or Administrator with a data-focused background

Advancement To:

Senior Vocational Analyst / Lead Analyst
Director of Institutional Effectiveness or Research
Data Analytics Manager (Education)

Lateral Moves:

Workforce Development Coordinator
Curriculum Development Specialist
Program Assessment Coordinator

Core Responsibilities

Primary Functions

Conduct comprehensive and longitudinal analysis of student data, including enrollment trends, retention rates, completion metrics, and demographic shifts, to identify patterns and inform strategic enrollment management.
Develop, manage, and maintain complex dashboards and data visualizations using tools like Tableau or Power BI to make key performance indicators (KPIs) accessible to non-technical stakeholders, including faculty and leadership.
Analyze local and regional labor market information (LMI) and industry trend data to assess the alignment of current vocational programs with workforce demands and identify opportunities for new program development.
Design, implement, and analyze data collection systems, including graduate follow-up surveys, employer satisfaction surveys, and student focus groups, to gather crucial qualitative and quantitative data on program effectiveness.
Prepare and submit mandatory compliance reports for federal, state, and local agencies (e.g., Perkins V, IPEDS, WIOA) and accrediting bodies, ensuring accuracy, timeliness, and adherence to all reporting requirements.
Collaborate with academic departments to establish and monitor student learning outcomes, and develop data-driven methods for assessing the effectiveness of curriculum and instructional strategies.
Lead research projects on student success initiatives, evaluating the impact of interventions such as tutoring, advising changes, or financial aid programs on student persistence and completion.
Extract, clean, and manipulate large datasets from the Student Information System (SIS) and other institutional databases to prepare them for detailed analysis and reporting.
Translate complex statistical findings into clear, concise, and compelling narratives, reports, and presentations for a variety of audiences, from faculty committees to the Board of Trustees.
Serve as the primary data resource for program review and accreditation self-study processes, providing the necessary evidence and analysis to support institutional claims of quality and effectiveness.
Monitor key performance metrics for specific grants and initiatives, providing regular progress reports to grant managers and funding agencies to ensure compliance and demonstrate impact.
Respond to a high volume of ad-hoc data requests from various internal departments, including marketing, finance, and student services, providing timely and accurate information to support their functions.
Evaluate the efficacy and ROI of different student recruitment and marketing campaigns by analyzing application, matriculation, and enrollment data.
Develop predictive models to identify students at risk of attrition, enabling proactive and targeted support interventions from student services and academic advisors.
Conduct equity-focused analysis to identify and address achievement gaps among different student sub-populations, ensuring all students have an equal opportunity to succeed.
Collaborate with the IT department to ensure data integrity and advocate for improvements in data governance, data definitions, and data collection processes across the institution.
Provide training and support to faculty and staff on how to access and interpret institutional data and dashboards, fostering a more data-informed culture across the school.
Stay current with emerging trends, technologies, and best practices in institutional research, data analytics, and career and technical education.
Manage the institutional research calendar, ensuring all cyclical and recurring reporting and analysis projects are planned for and completed on schedule.
Perform environmental scans of competitor institutions and programs, benchmarking performance and identifying strategic opportunities and threats.
Automate recurring data reports and processes using scripting or other tools to improve efficiency and allow for more time to be spent on in-depth, value-added analysis.

Secondary Functions

Support ad-hoc data requests and exploratory data analysis.
Contribute to the organization's data strategy and roadmap.
Collaborate with business units to translate data needs into engineering requirements.
Participate in sprint planning and agile ceremonies within the data engineering team.

Required Skills & Competencies

Hard Skills (Technical)

SQL Proficiency: Demonstrated ability to write complex SQL queries for data extraction, transformation, and aggregation from relational databases.
Data Visualization: Expertise in creating compelling and interactive dashboards and reports using tools like Tableau, Power BI, or Google Data Studio.
Statistical Software: Practical experience with at least one statistical package such as SPSS, SAS, R, or Python (with pandas, NumPy, scikit-learn).
Student Information Systems (SIS): Familiarity with querying and extracting data from common SIS platforms like Banner, PeopleSoft, or Colleague.
Advanced Spreadsheet Skills: Mastery of Microsoft Excel, including Power Query, Power Pivot, complex formulas, and macros for data manipulation and analysis.
Survey & Research Tools: Experience designing, administering, and analyzing surveys using platforms like Qualtrics or SurveyMonkey.
Compliance Reporting: Knowledge of federal and state reporting requirements for postsecondary education, such as IPEDS, Perkins, and NSC (National Student Clearinghouse).
Data Warehousing Concepts: A solid understanding of data warehousing principles, ETL processes, and dimensional modeling.
Labor Market Information (LMI) Tools: Ability to use LMI data sources (e.g., EMSI, Burning Glass, Bureau of Labor Statistics) to analyze workforce trends.
Statistical Analysis: Strong foundation in descriptive and inferential statistics, including regression analysis, t-tests, and ANOVA.
Programming/Scripting: Experience with a scripting language like Python or R for data cleaning, automation, and analysis is highly valuable.

Soft Skills

Analytical & Critical Thinking: The ability to dissect complex problems, see connections in data, and evaluate information from multiple perspectives.
Storytelling with Data: A talent for translating quantitative findings into a clear, compelling narrative that drives action and understanding.
Communication & Presentation: Excellent written and verbal communication skills, with the confidence to present to diverse audiences, from technical peers to executive leadership.
Stakeholder Management: The ability to build strong relationships with faculty, administrators, and staff, understanding their needs and managing their expectations.
Detail-Oriented & Meticulous: A keen eye for detail and a commitment to data accuracy and integrity, especially in high-stakes compliance reporting.
Curiosity & Problem-Solving: A natural inquisitiveness and a proactive approach to identifying institutional challenges and using data to find solutions.

Education & Experience

Educational Background

Minimum Education:

A Bachelor's Degree is required for this role.

Preferred Education:

A Master's Degree is highly preferred, as it often provides a deeper foundation in research methodologies and statistical analysis.

Relevant Fields of Study:

Data Science / Analytics
Statistics
Economics
Social Sciences (e.g., Sociology, Psychology)
Public Policy / Administration
Educational Research or Administration
Computer Science / Information Systems

Experience Requirements

Typical Experience Range:

3-5 years of professional experience in a role focused on data analysis, business intelligence, or institutional research.

Preferred:

Direct experience within an educational setting, particularly a community college, technical college, or vocational school, is highly desirable. Experience with educational data, accreditation, and compliance reporting will be a significant advantage.