Asks for

The ad says“Familiarity with reinforcement learning, bandits, or adaptive optimization concepts (applied or research-driven).”
The ad says“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.”
The ad says“Familiarity with reinforcement learning, bandits, or adaptive optimization concepts (applied or research-driven).”
The ad says“Strong foundation in econometrics, causal inference, and behavioral modeling.”
The ad says“Strong foundation in econometrics, causal inference, and behavioral modeling.”
The ad says“Deep understanding of price elasticity, choice modeling, and decision science.”
The ad says“Deep understanding of price elasticity, choice modeling, and decision science.”
The ad says“Strong foundation in econometrics, causal inference, and behavioral modeling.”
The ad says“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.”
The ad says“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.”
The ad says“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.”
The ad says“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.”
The ad says“Deep understanding of price elasticity, choice modeling, and decision science.”
The ad says“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.”
The ad says“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.”
The ad says“Familiarity with reinforcement learning, bandits, or adaptive optimization concepts (applied or research-driven).”
The ad says“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.”
The ad says“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.”
The ad says“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.”

Want to help us help others? We’re hiring!

GoFundMe is the world’s most powerful community for good, dedicated to helping people help each other. By uniting individuals and nonprofits in one place, GoFundMe makes it easy and safe for people to ask for help and support causes—for themselves and each other. Together, our community has raised more than $40 billion since 2010.

We’re looking for a Staff Data Scientist (Pricing) to serve as the senior individual contributor driving 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.

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.

The Job

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.

You

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.
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.

Preferred but not required

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.

Why you’ll love it here

Make an Impact: Be part of a mission-driven organization making a positive difference in millions of lives every year.
Innovative Environment: Work with a diverse, passionate, and talented team in a fast-paced, forward-thinking atmosphere.
Collaborative Team: Join a fun and collaborative team that works hard and celebrates success together.
Competitive Benefits: Enjoy competitive pay and comprehensive healthcare benefits.
Holistic Support: Enjoy financial assistance for things like hybrid work, family planning, along with generous parental leave, flexible time-off policies, and mental health and wellness resources to support your overall well-being.
Growth Opportunities: Participate in learning, development, and recognition programs to help you thrive and grow.
Commitment to DEI: Contribute to diversity, equity, and inclusion through ongoing initiatives and employee resource groups.
Community Engagement: Make a difference through our volunteering program.

We live by our core values: impatient to be great, find a way, earn trust every day, fueled by purpose. Be a part of something bigger with us!

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.

The annual U.S. salary range for this full-time position is $179,500 - $269,500. The company also offers equity and other benefits to employees, including healthcare, dental, vision, life insurance and 401(k) saving program. In addition to this wage, there are geolocation differentials that will increase pay depending on the work location. Additionally pay may vary depending on other factors including skills, experience, education, or training. Your recruiter can share more about the specific total compensation package based on your location during the hiring process.

If you require a reasonable accommodation to complete a job application or a job interview or to otherwise participate in the hiring process, please contact us at accommodationrequests@gofundme.com.

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.

Our annual “Year in Help” report reflects our community’s impact in advancing our mission of helping people help each other.

For recent company news and announcements, visit our Newsroom.

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.

We began using Metaview on March 10, 2026. The Metaview tool has been reviewed by an independent auditor. Results of the audit may be viewed here. The tool evaluates your professional experience, technical skills, education, and other qualifications using information collected directly from your submitted resume and application materials; all such data is retained in accordance with GoFundMe’s Personnel Privacy Notice and applicable legal requirements. If you would like to request an alternative selection process or a reasonable accommodation, please contact accommodationrequests@gofundme.com.