Responsible for implementing data strategy as developed in partnership with the Research, Learning, and Evaluation (RLE) team, and operationalizing data analysis to inform policy and local activities.

Responsibilities

• Analyze existing datasets held or licensed by the Foundation and recommend data deliverables while considering: 1) fit with the Foundation’s strategic priorities and research agenda, 2) sustainability, 3) data quality, 4) rigor, and 5) data justice.
• In partnership with RLE leadership, build strong relationships with local professionals who do “best-practice” work in institutional research, school accountability, assessment, school attendance and engagement, community data, business licensing, or others who are aligned with our strategic priorities.
• Recommend data management approaches that inform citywide learning and measure impact.
• Regularly gather community feedback related to the Foundation’s research and data agenda to identify emerging and ongoing data needs and make adjustments based on this input.
• Track ad-hoc data requests from external stakeholders, identifying themes, and recommending new data products and deliverables that address consistent needs.
• Consult about artificial intelligence and automation tools that improve internal and external reporting and efficiency. This may include vendor landscape analyses to identify vendors who can advance the Foundation’s research and data practices.
• Support the Foundation’s data strategy and operations while complying with GDPR, FERPA, PII, and CPA standards.

Skillset

• ​Bachelors​ or master’s degree in applied data science, computer information systems, or computer science with data science knowledge, required or equivalent years of experience. Data science, or computer science training or certification, preferred.
• At least five years of progressive experience in data-driven, applied social science activities, including data science, analytics, visualization and consulting across complex organizations.
• Demonstrated passion for advancing equitable and transformative solutions for the communities served by the Foundation, with clear alignment to the Kauffman Foundation’s credo, racial equity, diversity, and inclusion commitments, and strong ethical judgment.
• Familiarity with and interest in the Foundation’s substantive focus areas, such as regional economic development, entrepreneurship, and economic mobility.
• Proven ability to work effectively within and across diverse teams, and with stakeholders at all levels from a wide range of industries and backgrounds.
• Excellent communication skills, including strong interpersonal, written, and listening abilities; able to distill complex ideas into clear, concise, and actionable recommendations.
• Strong analytical, critical thinking, and problem-solving skills; able to translate open-ended questions into clear analytical plans and independently produce high-quality analyses, reports, and presentations.
• Familiarity with industry-standard datasets related to businesses, industries, and employment (e.g. BLS, U.S. Census Bureau, and related federal, state, and local data products, including an understanding of their strengths and limitations.
• Experience addressing common real-world data issues (e.g., coverage gaps, suppression, small cell sizes, data quality) using practical and defensible approaches; ability to apply an equity lens through appropriate disaggregation and contextualizing findings for impacted communities.
• Experience conducting quantitative analyses such as descriptive statistics, exploratory data analysis, predictive modeling, and spatial analysis, and translating findings into accessible visual and written outputs.
• Experience with statistical software, programming languages, and/or business intelligence tools such as R, Python, SQL, and working with APIs; familiarity with cloud environments (e.g., AWS) is a plus.
• Experience building reproducible analytic workflows (e.g., scripted data pulls via APIs reusable code, version control such as Git, and clear documentation) to support ongoing and repeatable analysis.
• Proficiency working with disparate datasets and coordinating data from diverse sources; comfort with database structures, data dictionaries, and data documentation.
• Demonstrated ability to manage multiple projects, prioritize effectively, and meet deadlines, with strong organizational skills, attention to detail, and understanding of project management tools and technology.
• Strong Excel skills (e.g., formulas, statistical analysis, PivotTables) and proficiency with standard productivity tools (e.g., Microsoft Office, Box, Slack); experience with Tableau or Power BI and Salesforce preferred.

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