Responsibilities

Own donation pricing and amount optimization end-to-end: Define the analytical strategy, modeling frameworks, and success metrics for pricing recommendations across product surfaces, balancing conversion, donation amounts, and long-term donor trust.
Model human behavior using economics and AI: Apply economic theory, behavioral science, and machine learning to understand donor decision-making, estimate elasticity, and predict responses to changes in product design and choice architecture.
Leverage non-transactional behavioral signals: Model sparse and indirect signals (e.g., navigation, hesitation, context, device, timing) to detect shifts in intent and interaction patterns beyond observed transactions.
Build adaptive and reinforcement-aware systems: Design models that learn over time using experimentation signals, feedback loops, and reinforcement concepts (e.g., contextual bandits or sequential decision-making) where appropriate.
Lead experimentation and causal learning: Partner with Product and Engineering to design robust experimentation and measurement frameworks, ensuring pricing and donation models are causal-aware, interpretable, and safe to deploy at scale.
Incorporate external data and context: Augment behavioral models with external datasets (macroeconomic indicators, seasonality, regional or temporal signals) to better understand and anticipate donor behavior.
Translate insights into action: Convert complex economic and behavioral analyses into deployable models, clear product recommendations, and measurable business impact.
Influence through storytelling and leadership: Communicate insights effectively to senior leaders, humanize donor behavior through narrative, and serve as a trusted thought partner on pricing and donation strategy.
Raise the technical bar: Set best practices for modeling rigor, validation, monitoring, and iteration; mentor other data scientists and elevate pricing science across the organization.
Experience & Education
Either a Ph.D. in Economics, Applied Economics, or a closely related quantitative field, demonstrating the ability to push the boundaries of applied research and translate theory into practical modeling approaches OR 8+ years of industry experience in data science, applied economics, pricing, marketplace optimization, or monetization at a high-tech digital company, with a proven track record of owning and scaling pricing or decisioning systems.
Deep experience applying economic reasoning, causal inference, and behavioral modeling to real-world decision-making problems.

Staff Data Scientist (Pricing) at Gofundme · LumiJobs

Staff Data Scientist (Pricing)

Responsibilities

Qualification

Preferred

Benefits

Company

Gofundme

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