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About the Role

GoFundMe is seeking a Staff Data Scientist to shape how the company uses data science to grow its impact across marketing, growth, and product. This senior individual contributor role will lead high-impact workstreams, focusing on improving audience strategy, acquisition, retention, personalization, experimentation, and investment efficiency. The role involves partnering with leaders across various departments to define technical strategy, build scalable frameworks, and translate complex analyses into actionable recommendations.

Responsibilities

Lead high-impact data science initiatives across marketing, growth, and product, from problem definition through methodology, execution, interpretation, and recommendation.
Define org-level technical strategy, identify high-leverage opportunities, and establish best practices for experimentation, causal measurement, modeling, AI-assisted development, and decision science.
Design, analyze, and interpret experiments and quasi-experiments; build scalable frameworks to estimate incrementality, treatment effects, and long-term business value.
Develop ML, uplift, heterogeneous treatment effect, and adaptive experimentation models to improve targeting, segmentation, personalization, lifecycle optimization, audience strategy, budget allocation, and product decisions.
Partner with Marketing, Growth, Sales, Finance, and Product to evaluate acquisition, retention, ROI, user journeys, funnels, marketplace dynamics, donation conversion, and engagement.
Use AI tools to accelerate prototyping, analysis, coding, debugging, documentation, and repetitive workflows without compromising quality, accuracy, or review standards.
Translate complex analyses into clear recommendations for technical, non-technical, and executive audiences.
Collaborate with Data, Analytics, and Product Engineering to improve instrumentation, data quality, experimentation infrastructure, and reusable data science workflows.
Mentor data scientists and analysts through design reviews, model reviews, methodology discussions, AI-enabled workflows, and shared best practices.

Requirements

8+ years of experience leading data science, applied statistics, or machine learning projects with measurable business impact.
Master’s degree or Ph.D. in a quantitative field, or equivalent applied experience coupled with a bachelor’s degree.
Experience with marketing, growth, marketplace, and/or product optimization problems.
Strong command of statistical inference, causal inference, uplift modeling, heterogeneous treatment effects, treatment/control frameworks, and incrementality measurement.
Experience applying machine learning to targeting, personalization, segmentation, recommendation, lifecycle optimization, or similar problems.
Familiarity with adaptive experimentation, including frequentist A/B tests, multi-arm bandits, contextual bandits, and/or related optimization methods.
Advanced proficiency with SQL and Python for data extraction, transformation, modeling, and analysis.
Experience using AI-assisted tools to increase the speed and quality of analysis, coding, iteration, and communication.
Ability to define technical strategy, identify reusable patterns, and raise the quality of data science work across teams.
Strong business judgment and stakeholder management skills.
Excellent communication and storytelling skills, including experience presenting to executive audiences.
Experience mentoring data scientists, analysts, or other technical team members.
Experience with marketing measurement methods such as media mix modeling, multi-touch attribution, channel incrementality, forecasting, budget allocation, optimization, or ROI modeling.
Experience with web, mobile, product, or marketplace analytics tools such as Amplitude, Google Analytics, Optimizely, or GrowthBook.
Familiarity with modern data platforms and workflows such as Snowflake, Databricks, dbt, Airflow, Git, Looker, Tableau, or similar tools.
Experience operationalizing AI or ML workflows with engineering partners.

Skills

Data Science
Applied Statistics
Machine Learning
Statistical Inference
Causal Inference
Uplift Modeling
Heterogeneous Treatment Effects
Incrementality Measurement
Targeting
Personalization
Segmentation
Recommendation Systems
Lifecycle Optimization
Adaptive Experimentation
A/B Testing
Multi-arm Bandits
Contextual Bandits
SQL
Python
AI-assisted Tools
Technical Strategy
Stakeholder Management
Communication
Storytelling
Mentoring
Media Mix Modeling
Multi-touch Attribution
Channel Incrementality
Forecasting
Budget Allocation
ROI Modeling
Amplitude
Google Analytics
Optimizely
GrowthBook
Snowflake
Databricks
dbt
Airflow
Git
Looker
Tableau

Location

San Francisco Bay Area

Work Type

Hybrid (3x a week in-office)
Full-time

Experience Level

Staff
8+ years

Education Level

Master’s degree or Ph.D. in a quantitative field
Bachelor's degree with equivalent applied experience

Salary/Compensations

$179,500 - $269,500

Benefits

Equity
Comprehensive healthcare benefits
Dental
Vision
Life insurance
401(k) saving program
Financial assistance for hybrid work
Family planning assistance
Generous parental leave
Flexible time-off policies
Mental health and wellness resources
Learning, development, and recognition programs
Volunteering program

About the Company

GoFundMe is the world's most powerful community for good, dedicated to helping people help each other.
GoFundMe has raised more than $40 billion since 2010.
GoFundMe partners with GoFundMe.org, an independent public charity, to extend reach and impact.
GoFundMe's core values are: impatient to be great, find a way, earn trust every day, fueled by purpose.

Equal Opportunity

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.