Senior Data Officer

RESPONSIBILITIES

Reporting directly to the Director of Research, the Senior Data Officer (SDO) implements data strategy in partnership with the Research, Learning, and Evaluation (RLE) team and operationalizes data analysis to inform policy and local activities. The role works closely with other RLE team members and Foundation associates in alignment with the Foundation’s mission, vision, and strategic priorities.

Specific

Responsibilities Include:

• Analyze existing datasets held or licensed by the Foundation and recommend data deliverables while considering fit with the Foundation’s strategic priorities, research agenda, sustainability, data quality, rigor, and 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 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 adjust based on this input.
• Track ad-hoc data requests from external stakeholders, identify themes, and recommend 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.

Travel:
This position may require some business travel.

Education:

Bachelor’s 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.

Work Experience:

At least five years of progressive experience in data-driven, applied social science activities, including data science, analytics, visualization, and consulting across complex organizations.

Incumbents for this position must be highly motivated, capable of self-direction, and able to work collaboratively in a team. Incumbents must exhibit a keen sense of responsibility and enjoy working with multiple demands, shifting priorities, and constant change.

• 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…