About The Position

Givzey is a rapidly growing technology company focused on the nonprofit sector, aiming to increase generosity through AI-powered donor engagement. Their platform, Version2.ai, features Autonomous AI fundraisers called Virtual Engagement Officers (VEOs) that manage donor portfolios, build relationships, and secure gifts independently. Givzey's Gift Agreement Platform also streamlines the process of securing and managing multi-year giving commitments. The Version2.ai platform is used by over 200 fundraising organizations and has facilitated over $10 million in gifts, with individual gifts reaching $100,000. This new role, Director of Fundraising Intelligence, will be responsible for analyzing market data derived from these deployments, providing insights to internal teams (Sales, Customer Success) and external stakeholders (customers, the broader fundraising sector). The role requires a blend of analytical skills and public-facing communication, including presenting findings at conferences and publishing research.

Requirements

  • 5+ years working with fundraising or advancement data (practitioner, analyst, or researcher in nonprofit, higher education, or healthcare philanthropy).
  • Deep fluency in advancement metrics: gift upgrades, major gift pipeline, lapse and reactivation, planned giving indicators, donor renewal rates.
  • Strong quantitative skills: ability to build and QA analysis, identify statistical significance, and discern real findings from noise.
  • Exceptional communication skills (written and verbal): ability to explain complex data findings concisely.
  • Demonstrated public speaking experience (conference presentations, webinars, panel participation, or equivalent).
  • Comfortable operating without a fully built infrastructure; ability to create process.
  • Proficiency in data tools beyond Excel (Python, R, SQL, Tableau, or similar).
  • Proven experience utilizing AI to assist in data projects.

Nice To Haves

  • Experience publishing original research, white papers, or thought leadership content in the fundraising or nonprofit sector.
  • Existing relationships or reputation within the advancement community (e.g., CASE Summit, AFP ICON, AHP membership).
  • Familiarity with AI, machine learning, or automation in a fundraising context.
  • Experience working at or with a SaaS company serving the nonprofit or higher education sector.

Responsibilities

  • Conduct meaningful market analysis of fundraising data.
  • Arm Sales and Customer Success teams with statistical insights.
  • Provide customers with deeper insights into benchmarks for success.
  • Identify cross-cutting insights about autonomous AI in fundraising and partner with the marketing team to share them.
  • Develop original research, including benchmarks, trend reports, sector comparisons, and giving behavior analysis.
  • Maintain intellectual rigor and align research with fundraising standards to ensure sector trust.
  • Develop and execute a strategy with the VP of Marketing to establish Version2.ai as the sector's most trusted source of data and insight on autonomous AI in fundraising.
  • Partner with marketing on session submission and delivery of speaking engagements at major advancement and fundraising conferences.
  • Write and publish original research, blog posts, LinkedIn content, and white papers in coordination with Marketing.
  • Build and cultivate a personal presence on LinkedIn.
  • Build a public-facing identity recognized as credible and independent.
  • Coordinate all external content and positioning with the Marketing team.
  • Analyze gift data across individual client deployments to surface meaningful performance metrics.
  • Partner with Customer Success Managers and the Expansion AE to build data-backed business cases for additional VEO deployments.
  • Translate raw numbers into compelling narratives for advancement leaders.
  • Develop a repeatable insight framework and tools for Customer Success Managers.
  • Partner with Account Executives to build customized ROI cases for prospects.
  • Model projected outcomes based on comparable client performance.
  • Participate in late-stage prospect conversations as needed.
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