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Seniority (Information technology, software development, data, Non-profit, social work)
© Fuzu Ltd
GiveDirectly, Inc
Non-profit + 1 more
Description
Required
- 8+ years of experience in analytics, data science, or quantitative strategy roles, including a track record of driving marketing, growth, or fundraising performance through analytics
- Strong experience setting vision and priorities for data products from significant ambiguity
- Strong systems thinking and experience designing measurement systems that compound in value and reduce recurring friction
- Advanced SQL skills and demonstrated experience building production-grade data models in a data warehouse
- Strong Python proficiency
- Experience building forecasting models (e.g., revenue, LTV, retention)
- Experimentation and performance measurement experience (e.g., A/B testing, quasi-experimental methods, ROI evaluation)
- Ability to navigate ambiguity and independently shape how data informs organizational strategy
Responsibilities
Data Product and Metrics Ownership
- Set vision and priorities for how data supports fundraising and marketing strategy, based on a deep understanding of GiveDirectly’s fundraising model, donor lifecycle, and growth strategy, across revenue streams
- Define, standardize, and document core fundraising and marketing KPIs (e.g., retention, LTV, revenue forecasting metrics) to drive fundraising goals
- Design and build robust data models in the warehouse that serve as the source of truth for fundraising reporting - weekly, monthly, quarterly and annually
- Establish clear, trusted source-of-truth datasets and metric logic used consistently across Fundraising, Finance, and Leadership, continually folding learnings in to update the metrics and definitions
- Identify recurring analytical needs and convert them into scalable, automated data products
- Scope and prioritize fundraising data products in partnership with Fundraising and Marketing Data stakeholders
- Partner with data engineering on upstream data quality and pipeline improvements, while owning the downstream analytical layer
- Continuously reduce ad hoc reporting by investing in durable systems that compound in value over time
Strategic Fundraising and Marketing Analytics
- Serve as the primary data partner to fundraising and marketing leadership, informing strategy across acquisition, retention, and revenue expansion
- Build and maintain revenue forecasts and donor cohort models to guide annual planning and budget allocation
- Support channel investment decisions with clear ROI frameworks, experiment design, and performance analysis
- Proactively surface decision-relevant insights, even when questions are not fully formed
Donor & Revenue Insights
- Conduct deep-dive analyses into donor cohorts, retention drivers, churn patterns, and cost per dollar raised to drive continuous improvement on fundraising performance
- Evaluate marketing and fundraising initiatives using appropriate analytical methods (including experimentation where feasible, though not all channels support large-scale testing)
- Translate complex analyses into clear recommendations for non-technical stakeholders that drive fundraising improvements
- Surface high-leverage opportunities to improve conversion, retention, and revenue durability
Data Infrastructure & Platform Contribution
- Collaborate with data engineers and analytics peers to improve data quality, access, and trust
- Partner with the Salesforce Lead to ensure CRM data structure and integrity support accurate reporting and scalable downstream modeling
- Contribute to the long-term roadmap for fundraising data architecture, ensuring systems are designed for scalability and compounding insight generation over time
- Contribute to improvements in GiveDirectly’s data capabilities such as adopting conversational analytics
- Maintain high standards of analytical rigor, documentation, and reproducibility
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