Lead Data Scientist

📋 Description

• Prove causality via randomized experiments and uplift analysis.
• Build predictive and forecasting models for donor behavior and outcomes.
• Own model quality, evaluation, and monitoring across the lifecycle.
• Deploy ML models to production; manage the ML lifecycle on Databricks and MLflow.
• Set the data science technical direction; define methods and tooling for rigor.
• Partner across the stack; collaborate with data engineers and AI engineers.

🎯 Requirements

• 8+ years of applied data science shipping models.
• Causal inference and experimentation with A/B testing.
• Predictive and statistical modeling: churn, LTV, time-series.
• Strong Python and SQL; familiar with scikit-learn and gradient boosting.
• Production ML sensibility: deployment, versioning, monitoring (Langfuse/MLflow).
• Lakehouse data platform fluency; Databricks; data modeling.

🎁 Benefits

• Health, vision, and dental options.
• Comprehensive PTO, flex days, holidays, and parental leave.
• 401k match to help invest in your future.
• Equipment shipped to your door.