Lead Data Scientist

Applied data science experience:

8+ years building data science and machine learning that shipped to production and moved a real metric—not models that stalled in a notebook.

You know why measuring impact against KPIs without a control group is the most common way to learn the wrong lesson.

Predictive and statistical modeling:

propensity, churn and retention, lifetime value, time-series and forecasting, and calibration—with the judgment to reach for the simplest model that works.

Strong Python and SQL,

Health + Wellness

You’ll have access to generous health, vision, and dental insurance options as well as HealthiestYou, a healthcare service that offers convenient, confidential access to quality doctors 24/7, anytime, anywhere.

As a Data Science Lead at Bloomerang, you'll own the intelligence layer on top of the Unified Data Foundation (UDF)—the models, experiments, and measurement that turn the data of 24,000+ nonprofits into products they can trust.

Reporting to the Director of AI Product Engineering, you'll set the technical direction for data science across the Bloomerang Giving Platform: the causal measurement that proves what actually works, the predictive and forecasting models that anticipate donor behavior, the evaluation that keeps our AI products trustworthy, and the ML platform that gets all of it to production.

Data is the moat; intelligence is the castle.

You'll prove causation instead of settling for correlation, set the bar for how models are built, measured, and shipped, and partner daily with data engineers, AI engineers, and product.

You'll bring AI-native habits into how you build, test, and reason.

Design and run the experimentation engine—randomized holdouts, uplift measurement, significance and power—so we can claim a fundraising action caused a lift in retention or giving, not that it happened alongside one.

you're energized by the pace of AI-driven change—including LLM and agent evaluation—and you bring that energy into the team.

Leadership & Ownership

Technical leadership without the org chart:

you set direction through the clarity and rigor of your work, your standards, and your influence. This is a principal-level individual-contributor seat, not a people-management one.

Quality-first instincts:

you build evaluation, monitoring, and honest uncertainty in from day one. You'd rather ship a calibrated “we're not sure yet” than a confident answer that's wrong.