Pricing Data Scientist - Elasticity, Experiments & AI

GoFundMe; San Francisco (CA); Hybrid; USD 180,000 - 270,000; Full time

Job summary

GoFundMe is hiring a Staff Data Scientist (Pricing) to drive pricing strategy, experimentation, and AI deployment for donation pricing and yield optimization. The role blends economics, behavioral science, and machine learning to improve donation conversion, amounts, and donor experience.

The candidate will lead pricing projects across product surfaces and work with Product and Engineering on robust experimentation and deployment.

Qualifications

• PhD in Economics or related quantitative field (or 8+ years in data science/economics pricing).
• Deep experience with econometrics, causal inference, and behavioral modeling.
• Ability to own ambiguous, high-impact problems and deliver measurable outcomes.

Responsibilities

• Define analytical strategy, modeling frameworks, and metrics for pricing and yield optimization.
• Model donor behavior with economics, AI, and experimentation to estimate elasticity and responses.
• Incorporate non-transactional signals to detect shifts in intent and interaction patterns.
• Design adaptive models using experimentation signals and reinforcement concepts.
• Lead experimentation and causal learning with Product and Engineering teams to ensure robust, interpretable pricing models.
• Augment models with external data like macro indicators and seasonality to improve forecasts.
• Translate insights into actionable recommendations and measurable business impact.
• Communicate findings to senior leaders and influence pricing strategy.
• Mentor other data scientists and elevate pricing science across the org.

Skills

Economics

Causal inference

Behavioral modeling

Experimentation

Reinforcement learning

Storytelling

Leadership

Product collaboration

Education

PhD in Economics or related quantitative field

Tools

Python

SQL

Stan PyMC

LLM tools

Job description

GoFundMe is hiring a Staff Data Scientist (Pricing) to drive pricing strategy, experimentation, and AI deployment for donation pricing and yield optimization. The role blends economics, behavioral science, and machine learning to improve donation conversion, amounts, and donor experience.

The candidate will lead pricing projects across product surfaces and work with Product and Engineering on robust experimentation and deployment.