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
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
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
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
Requirements
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.
Tech Stack
Python
SQL
Benefits
A positive and supportive team with opportunities for advancement
A demonstrated commitment to helping all staff develop and grow
A competitive salary, including bonus
A robust health benefits plan (exact details will vary by country)
Flexible paid time off
Allowances for desk set-up and learning and development