Lead Data Scientist

Bloomerang

Lead Data Scientist at Bloomerang developing models and experimentation systems for nonprofits. Collaborate with data engineers and AI engineers to drive donor engagement and retention.

Posted 7/17/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $138,100 - $230,200 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in designing and managing predictive models and experimentation engines for fundraising, with a strong focus on model quality, evaluation, and collaboration with data engineering teams. Proficient in deploying and monitoring production-level machine learning models using modern tools and methodologies.

Highest-signal resume keywords

Data Science ExperiencePredictive ModelingPython ProficiencyML Lifecycle ManagementA/B Testing Expertise

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Predictive ModelingStatistical ModelingA/B TestingTime-Series ForecastingModel EvaluationMachine LearningData AnalysisModel DeploymentPerformance MonitoringTreatment-Effect Modeling

Tools & Technologies

DatabricksMLflowLangfuseScikit-LearnSQL

Industry Keywords

FundraisingDonor Lifetime ValueRetentionExperimentation EngineData Engineering

Tech Stack

Tools & technologies

PythonScikit-LearnSQL

About the role

Key responsibilities & impact

Design and run the experimentation engine for fundraising actions.
Build predictive and forecasting models that drive donor lifetime value and retention.
Own model quality and evaluation for trustworthy AI products.
Manage ML lifecycle on Databricks and MLflow including model training and performance monitoring.
Define technical direction for data science with high standards and rigor.
Partner daily with data engineers and AI engineers.

Requirements

What you’ll need

8+ years applied data science experience with production-level models that moved metrics.
Deep hands-on work with A/B testing, randomized holdouts, uplift and treatment-effect modeling.
Proficiency in predictive and statistical modeling (e.g., lifetime value, time-series forecasting).
Strong Python and SQL skills; fluency with modern ML and statistics stack (e.g., scikit-learn).
Experience deploying, versioning, and monitoring production ML models (Langfuse, MLflow).
Comfortable working on a lakehouse (Databricks preferred) and collaborating on data models.

Benefits

Comp & perks

Health + Wellness: Access to generous health, vision, and dental insurance options, and HealthiestYou healthcare service.
Time Off: Competitive PTO package including 20 PTO days, 3 flex days, 4 optional volunteer days, 12 paid holidays, and paid parental leave.
401k: 401k match to help invest in your future.
Equipment: Everything needed for success shipped to your door.