Lead Data Scientist
Core
Own the intelligence layer on top of the Unified Data Foundation, building causal measurement, predictive/forecasting models, and ML platform infrastructure for 24,000+ nonprofits to prove fundraising impact and anticipate donor behavior.
Role type
Principal-level individual contributor Lead Data Scientist
Builds
Causal measurement engines, predictive models for donor lifetime value/retention, and production ML pipelines on Databricks/MLflow
Domain
Nonprofit fundraising / Machine Learning / Causal Inference
Deliverable
production ML models
Required skills
Causal inference and experimentation (A/B testing, uplift modeling), Predictive and statistical modeling (propensity, churn, time-series), Python, SQL, Production ML lifecycle management (deployment, monitoring, drift detection), Modern data platform fluency (lakehouse architecture)
Preferred skills
LLM and agent evaluation frameworks, Data Vault 2.0 or medallion lakehouse modeling
Technologies
Databricks, MLflow, Langfuse, scikit-learn, gradient boosting, Claude Code, Cursor
Responsibilities
Design and run the experimentation engine (randomized holdouts, significance analysis), Build predictive models for donor behavior and forecasting, Own model quality, evaluation, and monitoring, Get models to production and maintain health, Set technical direction for data science methods and tooling, Partner with data engineers and AI engineers
Seniority
Principal, hands-on IC
