GoFundMe · 3 hours ago
Staff Data Scientist, Pricing
San Francisco, CA
Full-time
Hybrid
Lead/Staff
$180K/yr - $270K/yr
8+ years expGoFundMe is the world’s most powerful community for good, dedicated to helping people help each other. They are seeking a Staff Data Scientist, Pricing to drive the science, strategy, experimentation, and AI deployment behind pricing and yield optimization, focusing on optimizing donation conversion and donor experience across the product.
CrowdfundingInternetPeer to Peer
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
Qualification
Required
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
Demonstrated ability to own ambiguous, high-impact problems and deliver measurable business outcomes
Strong foundation in econometrics, causal inference, and behavioral modeling
Deep understanding of price elasticity, choice modeling, and decision science
Experience modeling noisy, sparse, or non-transactional behavioral data
Hands-on experience designing and interpreting experiments and causal signals
Familiarity with reinforcement learning, bandits, or adaptive optimization concepts (applied or research-driven)
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
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
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
Comfortable influencing product direction and executive decision-making
Demonstrated ability to lead without authority and elevate team practices
Preferred
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
Benefits
Competitive pay and comprehensive healthcare benefits
Financial assistance for things like hybrid work
Family planning
Generous parental leave
Flexible time-off policies
Mental health and wellness resources
Learning, development, and recognition programs
Volunteering program
Company
GoFundMe
GoFundMe is the world’s largest fundraising platform, helping people, causes, and charities raise money fast and efficiently.
201-500 employees
H1B Sponsorship
GoFundMe has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (19)
2024 (10)
2023 (10)
2022 (9)
2021 (9)
2020 (2)
Funding
Current Stage
Growth StageTotal Funding
unknown2015-07-02Series A
2014-04-01Series Unknown
Leadership Team
Timothy Cadogan
Chief Executive Officer
Steve Froehlich
Chief Customer Growth Officer
Recent News
2026-01-06
Markets | Mail Online
2025-12-29
2025-12-15
Company data provided by crunchbase