Provide technical expertise to ensure the quality and accuracy of data to guide future planning.

Responsibilities

• Provide data support and analysis for continuous improvement and reporting to an assigned portfolio of programs.
• Use data analysis to generate quantitative/qualitative reports, using visualization tools such as Tableau.
• Assist in interpretation and dissemination of data to inform development, delivery and continuous improvement of grant services.
• Continuously review data to identify, analyze and assist in the interpretation of trends or patterns.
• Ensure integrity of data by verifying data quality and accuracy.
• Conduct gap analysis using principles of Results Based Accountability.
• Maintain updated need-based data for current team programs and programmatic ad hoc requests.
• Anticipate data needs of programs and ensure that needs are adequately met.
• Conduct ongoing data, data source, and evaluation process audits.
• Adhere to FERPA regulations, ensuring confidentiality and privacy of sensitive data.
• Provide literacy and database operations training to staff.
• Other roles/duties will be assigned as necessary to assist and support in the attainment of our mission, All Rural Students Succeed.

Skillset

• Associate’s degree required in Statistics, Mathematics, Computer Science, Data Science or Analytics, Data Visualization, Social Sciences, or a related field; Bachelor’s degree preferred.
• A minimum of three years of experience in data analysis, aggregation, visualization, dissemination, and reporting is required with a bachelor’s degree. An associate degree in a related field requires a minimum of five years of relevant experience.
• Demonstrated knowledge and skills regarding technology and statistical analysis.
• Knowledge of database operations and management.
• Ability to maintain confidentiality.
• Demonstrated analytical skills.
• Extensive experience with Microsoft Office.
• Familiarity with data visualization software.
• Ability to work independently as well as in a team setting.
• Clear written and oral communication skills.
• Experience with statistical programming languages such as Python, Stata, or R.
• Experience with SQL.

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