The Title III, Data Analyst performs professional-level analytical work in support of the Title III Strengthening Institutions Program. The position is responsible for developing and maintaining data systems; conducting quantitative analyses; producing institutional and federally required reports; and supporting performance measurements related to enrollment, retention, persistence, and graduation outcomes. Work involves extracting and managing data from institutional systems; applying statistical and predictive modeling techniques; ensuring data integrity and regulatory compliance; and providing analytical decision support to Title III leadership and university stakeholders. The position exercises independent judgment in selecting analytical methodologies, interpreting findings, and communicating results within established grant and institutional guidelines. Essential Job Functions Data Management and Infrastructure Development:Design, develop, and maintain structured datasets and data workflows supporting Title III initiatives. Extract, clean, validate, and integrate data from institutional systems and external sources. Develop documentation, data dictionaries, and reproducible processes to ensure continuity and accuracy. Advanced Data Analysis and Predictive Modeling:Conduct descriptive, inferential, and predictive analyses related to student success metrics. Develop and refine statistical models to identify trends and assess program effectiveness. Apply appropriate statistical methodologies and validate analytical outputs. Reporting and Visualization:Prepare recurring and ad hoc reports required for internal leadership and federal grant reporting. Develop dashboards and visualizations to communicate key performance indicators and trends. Present analytical findings in formats suitable for technical and non-technical audiences. Strategic and Operational Decision Support:Collaborate with Title III leadership and campus stakeholders to define data needs and performance measures. Provide analytical insight to inform program planning and continuous improvement efforts. Support strategic planning and evaluation initiatives within the Title III Office. Data Governance, Compliance, and Quality Assurance:Ensure compliance with FERPA, federal reporting standards, and institutional data governance policies. Conduct data validation procedures to maintain integrity, consistency, and reliability of data outputs. Grant Evaluation and Performance Monitoring:Monitor performance metrics aligned with Title III objectives. Assist with preparation and documentation of federal performance reports and audit-related materials. Minimum and Desired Qualifications Minimum Qualifications:Bachelor’s degree in data Analytics, Statistics, Computer Science, Information Systems, Mathematics, or a closely related STEM field. Two (2) years of professional experience in data analysis, institutional research, business intelligence, or a related analytical role; may be replaced with a master’s degree in a closely related STEM field. Demonstrated proficiency in at least one analytical programming language (e.g., Python, R) and structured query language (SQL). Experience working with relational databases and large structured datasets. Experience extracting, cleaning, validating, and transforming data from multiple sources. Experience preparing analytical reports, summaries, or dashboards for operational or strategic decision-making. Knowledge of statistical analysis principles and quantitative methodologies. Strong analytical, organizational, and problem-solving skills. Ability to communicate technical findings effectively to non-technical audiences. Ability to maintain confidentiality and comply with FERPA and institutional data governance standards. Desired Qualifications: Master’s degree in Data Science, Statistics, Analytics, or related field. Experience in higher education analytics, institutional research, or student success initiatives. Experience supporting federally funded grant reporting (e.g., Title III, Title V, NSF). Experience developing predictive models (e.g., logistic regression, cohort modeling, time-series analysis, A/ B testing). Experience with data visualization platforms (e.g., Power BI, Tableau, or similar business intelligence tools). Experience documenting data processes, creating data dictionaries, or supporting audit/reporting requirements.