National Data Analyst

Duties & Responsibilities

• Design, enhance, and maintain critical academic and operational data sets and systems for Great Hearts.
• Use descriptive and inferential statistical tools to analyze data sets, identify trends and patterns, and generate insights that support diagnostic, predictive, and strategic decision-making.
• Contextualize Great Hearts’ data, where appropriate, through comparison with local and national statistics, benchmarks, and trends.
• Prepare reports and presentations for executive leadership and other stakeholders that communicate trends, patterns, findings, and predictions clearly to non-specialist audiences.
• Support timely and compliant annual data reporting to grant-makers, state and federal agencies, and other external stakeholders.
• Provide accurate and insightful academic and operational data analysis to Great Hearts teams in support of planning, improvement, accountability, and decision-making.
• Aid in the administration and refinement of the annual Great Hearts survey cycle to support continual organizational improvement.
• Collaborate with organizational leaders to identify opportunities for process improvement, recommend system modifications, and strengthen policies and practices for data governance.
• Build collaborative working relationships with academic, operational, and regional leaders to ensure data products and reporting practices meet organizational needs.
• Perform additional duties as assigned.

Qualifications, Competencies, And Strengths

• Advanced undergraduate/graduate-level statistical, data science, and research design skills (demonstrated either by formal qualifications or verifiable work product).
• Familiarity with K-12 settings and policies and key K-12 data sources; 2 years direct experience in a K-12 setting is desirable but not essential.
• Expertise in data collection, cleaning, analysis, and interpretation.
• Experience with visualization and analysis tools and packages such as Power BI, Tableau, Qualtrics; and in communicating data science concepts to non-technical audiences.
• Experience using statistical computer languages such as e.g. R, Python, SQL, or SPSS, to manipulate data and draw insights from large data sets is highly preferred.
• Experience working with and creating data architectures.
• Understanding of key principles of research design and familiarity with quantitative and qualitative methodologies.
• Knowledge of statistical techniques and concepts (regression, properties of distributions, statistical significance, sampling, etc.) and experience with applications.
• Knowledge of sound survey design.
• Excellent written and verbal communication skills, including the ability to communicate data science concepts clearly to non-technical audiences.
• A drive to learn and master new technologies and techniques.

Virtuous Ethos

• Virtuous Ethos
• Disciplined work ethic
• Committed spirit of servant leadership
• Excellent communications skills
• Effective relational skills
• Humble attitude of collaboration and partnership
• Precise decision-making practices