Staff Data Scientist, GoFundMe

• 8+ years in data science roles with a strong focus on marketing or growth analytics
• Master’s or Ph.D. in a quantitative discipline (Statistics, Mathematics, Economics, Engineering, Physics) or equivalent practical experience
• Advanced proficiency in Python (NumPy, pandas, scikit-learn) and SQL (window functions, performance tuning)
• Hands-on experience designing, analyzing, and interpreting A/B tests and experimentation frameworks
• Expertise in statistical inference, causal modeling (regression, propensity scoring), uplift modeling, and marketing attribution models (multi-touch attribution, Markov chains)
• Proven track record in time-series forecasting and budget allocation models
• Familiarity with ETL frameworks, data warehousing, and APIs; hands-on experience with Databricks and Snowflake is a plus
• Data visualization skills using Looker or equivalent BI tools; strong storytelling and presentation abilities
• Exceptional communication skills: able to influence non-technical stakeholders and present complex analyses to executive audiences
• Demonstrated ability to define technical strategy, elevate team practices, and drive high-impact initiatives
• Experience mentoring and developing junior data professionals

Desirable

• Join us! GoFundMe is looking for a Staff Data Scientist to strengthen our marketing data science and analytics initiatives and enhance data science operations throughout the company
• You will work with a skilled team to make a significant impact for both our users and our business
• Lead end-to-end data science projects: gather requirements, perform feature engineering, model development, validation, and deployment
• Define and promote technical best practices in tools, systems, and processes (e.g., model versioning, scalable pipelines, experimentation frameworks)
• Drive R&D initiatives: explore novel modeling approaches, assess emerging techniques, and prototype innovative solutions for marketing challenges
• Build, monitor, and report on key marketing KPIs; develop dashboards and present emerging trends and strategic recommendations to senior leadership
• Apply advanced analytical techniques: A/B testing, causal inference, uplift modeling, clustering, time-series forecasting to solve high-impact marketing challenges
• Partner with Product, Growth, Finance, and Engineering teams to identify and prioritize new analytics opportunities that drive user acquisition and revenue
• Develop forecasting and ROI models to optimize budget allocation and inform roadmap prioritization
• Collaborate with data engineering to design robust instrumentation, ETL processes, and data-quality monitoring
• Mentor and coach junior data scientists and analysts; lead code reviews, knowledge-sharing sessions, and onboarding activities
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