GoFundMe is looking to architect and lead the next generation of marketing data science to build and scale the foundations of applied data science and AI that empower Marketing, Growth, and Finance teams to make high-confidence, ROI-positive investment decisions.
Requirements
- Advanced proficiency in Python (NumPy, pandas, scikit-learn) and SQL (window functions, optimization).
- Deep experience with experimentation frameworks: A/B testing, causal inference, uplift modeling, and attribution models.
- Proven success in forecasting, optimization, and budget allocation models for marketing and growth functions.
- Hands-on with data platforms (Snowflake, Databricks) and BI tools (Looker, Tableau, or equivalent).
- Familiarity with experimentation and web/mobile analytics platforms (Optimizely, GrowthBook, Google Analytics, Amplitude).
- Experience integrating with marketing APIs (Google, Meta, programmatic platforms) for campaign optimization.
- Prior exposure to generative AI or LLMs in marketing use cases (e.g., personalization, targeting, creative analysis).
Responsibilities
- Build a strong AI and data science foundation: Develop scalable pipelines, reusable modeling frameworks, and robust experimentation platforms to support marketing and growth decision-making.
- Lead end-to-end data science & AI projects: From requirements gathering through feature engineering, modeling, validation, deployment, and monitoring.
- Establish best practices: Champion standards in model governance, reproducibility, data quality, and system reliability to ensure sustainable and trustworthy AI adoption.
- Drive marketing science innovation: Apply advanced methods—causal inference, uplift modeling, multi-touch attribution, and media mix modeling—to unlock insights and optimize spend.
- Advance forecasting & ROI modeling: Deliver budget allocation frameworks and predictive models that guide long-term roadmap planning and marketing efficiency.
- Push the frontier of applied AI in marketing: Evaluate emerging generative and predictive AI approaches for audience segmentation, creative optimization, personalization, and campaign efficiency.
- Familiarity with ML ops practices: version control, model monitoring, scalable ETL frameworks.
Other
- 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.
- 8+ years of experience in data science roles with direct impact on marketing, growth, or revenue optimization.
- Master’s or Ph.D. in a quantitative field (Statistics, Mathematics, Economics, Computer Science, Physics, Operations Research or related), or equivalent applied experience.
- Strong data storytelling and executive presentation abilities.
