Research Analyst

Compensation Range:

Position Summary

The Research Analyst is critical in leveraging research methods to support data-driven decision-making across the institution. The ideal candidate will possess a strong research and analytical background, coupled with experience in applying AI technologies to extract meaningful insights from complex datasets, ultimately driving initiatives that enhance student success.

Essential Functions:

Data Collection and Management

• Collaborate with cross-functional teams to identify, collect, and manage diverse data sources, including student demographics, academic performance, engagement metrics, and survey data.
• Ensure data integrity and accuracy through rigorous data cleaning, validation, and transformation processes.
• Implement and maintain data pipelines and integration processes to streamline data flow across institutional systems.

Advanced Data Analysis

• Familiarity with propensity score matching methodology in matched pairs analysis.
• Apply predictive analytics to model student outcomes, identifying at-risk students and recommending targeted interventions.
• Generate hypotheses and inform strategic decisions regarding student engagement, retention, and achievement.

Data Visualization and Reporting

• Develop interactive dashboards and visualizations using tools such as Power BI, or custom-built solutions, enabling stakeholders to explore and interpret key metrics and trends.
• Create comprehensive reports and presentations that communicate complex data insights in a clear and actionable manner to university leadership, faculty, and staff.
• Continuously enhance reporting tools and methodologies to meet the evolving needs of the institution.

AI-Driven Insights and Innovation

• Stay current with the latest advancements in AI, exploring new tools and techniques that can be applied to improve our research processes.
• Collaborate with academic departments and student services to design and implement AI-driven strategies that support student success.

Collaboration and Stakeholder Engagement

• Work closely with university departments, including academic affairs, student services, and IT, to understand their data-informed decision needs.
• Represent the research team in meetings and discussions, effectively communicating technical insights to non-technical stakeholders.
• Provide training and support to faculty and staff on data interpretation and the use of analytical tools.

Independent Work and Team Representation

• Work independently on assigned projects, managing time effectively and ensuring high-quality outputs without constant supervision.
• Represent the research team in cross-functional collaborations with university departments, effectively communicating insights and recommendations.
• Provide expert advice on data analysis methodologies to faculty, staff, and other stakeholders as needed.
• Other duties as assigned.

Supervisory Responsibilities: N/A

Requirements:

Education & Experience:

• Bachelor’s degree in data science, Statistics, Computer Science, or a related field, required.
• Master’s degree highly preferred.
• Minimum of three (3) to five (5) …