Staff Data Scientist (Pricing)

About the role

The Staff Data Scientist (Pricing) will drive the science, strategy, experimentation, and AI deployment behind pricing and yield optimization at GoFundMe. This role sits at the intersection of economics, behavioral science, experimentation, and machine learning, with direct responsibility for optimizing donation conversion, donation amounts, and donor experience across the product.

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.

Requirements

Candidates considered for this role will be located in the San Francisco Bay Area. There will be an in-office requirement of 3x a week.

Qualifications

• 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.

Core Skills

• 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).

Technical Skills

• 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.

Leadership & Collaboration

• 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.

Benefits

• The annual U.S. salary range for this full-time position is $179,500 - $269,500.
• Competitive benefits including healthcare, dental, vision, life insurance, and 401(k) saving program.
• Geolocation differentials may apply to increase pay depending on the work location.
• Additional pay may vary depending on other factors including skills, experience, education, or training.
• Participation in learning, development, and recognition programs to help you thrive and grow.
• Commitment to DEI through ongoing initiatives and employee resource groups.
• Volunteering opportunities to make a difference.

Company Culture

We are committed to creating a diverse and inclusive workplace where everyone feels valued and respected. We believe that a strong culture is essential for building a successful organization and fostering innovation. We strive to create an environment where everyone can bring their whole selves to work and feel empowered to contribute their unique perspectives and ideas.

Equal Opportunity Employer

GoFundMe is proud to be an equal opportunity employer that actively pursues candidates of diverse backgrounds and experiences. We do not discriminate on the basis of race, color, religion, ethnicity, nationality or national origin, sex, sexual orientation, gender, gender identity or expression, pregnancy status, marital status, age, medical condition, mental or physical disability, or military or veteran status.

Global Data Privacy Notice for Job Candidates and Applicants

Depending on your location, the General Data Protection Regulation (GDPR) or certain US privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available here. By submitting your application, you are agreeing to our use and processing of your data as required.

Learn More About GoFundMe

We’re proud to partner with GoFundMe.org, an independent public charity, to extend the reach and impact of our generous community, while helping drive critical social change. You can learn more about GoFundMe.org’s activities and impact in their FY ‘25 annual report.

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Metaview as part of our hiring process for jobs in NYC and certain features may qualify it as an automated employment decision tool (AEDT), as defined by New York City Local Law 144. As part of the hiring process, we provide Metaview with job requirements and candidate submitted resumes and application materials to assist in evaluating job-related qualifications. While this tool is used to improve efficiency and support our recruiting personnel, all final hiring decisions are made by GoFundMe employees.