Staff Data Scientist (Pricing)

Join GoFundMe as a Staff Data Scientist, Pricing. In this role, you will drive the science, strategy, experimentation, and AI deployment behind pricing and yield optimization. You will own donation pricing and amount optimization end-to-end, model human behavior using economics and AI, and lead experimentation and causal learning. You will also translate insights into action, influence through storytelling and leadership, and raise the technical bar. This position offers a wide range of benefits, including health insurance, wellness reimbursement, and a 401(k) retirement plan with company matching.

• Définir la stratégie analytique, les cadres de modélisation et les indicateurs de succès pour les recommandations de tarification.
• Appliquer la théorie économique, la science comportementale et l'apprentissage automatique pour comprendre la prise de décision des donateurs.
• Concevoir des modèles qui apprennent au fil du temps en utilisant des signaux d'expérimentation, des boucles de rétroaction et des concepts de renforcement.
• Familiarity with reinforcement learning, bandits, or adaptive optimization concepts (applied or research-driven)
• Deep experience applying economic reasoning, causal inference, and behavioral modeling to real-world decision-making problems
• Demonstrated ability to leverage modern AI tools and coding agents (e.g., LLM-based assistants, autonomous or semi-autonomous coding agents, model-driven feature generation, synthetic data generation) to accelerate research, prototyping, and productionization of models
• Deep understanding of price elasticity, choice modeling, and decision science
• Experience designing or applying LLM-based or AI-assisted solutions to complex decisioning problems (e.g., feature extraction from unstructured data, rapid experimentation, simulation, or model orchestration), beyond basic prompt usage
• Exceptional ability to tell clear, compelling stories from complex data
• Hands-on experience designing and interpreting experiments and causal signals
• Demonstrated ability to own ambiguous, high-impact problems and deliver measurable business outcomes
• Demonstrated ability to lead without authority and elevate team practices
• Experience modeling noisy, sparse, or non-transactional behavioral data
• Strong foundation in econometrics, causal inference, and behavioral modeling
• 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
• Advanced proficiency in Python (pandas, NumPy, scikit-learn, PyMC/Stan or equivalent) and SQL, with the ability to build, validate, and iterate on complex analytical and modeling workflows
• Comfortable influencing product direction and executive decision-making
• Experience in consumer pricing, marketplaces, or digital payments/donations
• Experience partnering with engineering to productionize models and AI-driven systems, including monitoring, evaluation, and iteration in live environments
• Familiarity with modern data platforms (Snowflake, Databricks) and experimentation infrastructure; experience with model versioning and validation is a plus
• Strong data visualization, documentation, and presentation skills, with an emphasis on clarity and executive-ready communication