Bloomerang - Lead Data Scientist
Requirements
• Technical Depth • Technical Depth • 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. • Causal inference and experimentation: deep, hands-on work with A/B testing, randomized holdouts, uplift and treatment-effect modeling, and significance and power analysis. You know why measuring impact against KPIs without a control group is the most common way to learn the wrong lesson. • Causal inference and experimentation: • 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. • Predictive and statistical modeling: • Strong Python and SQL, and fluency with the modern ML and statistics stack (e.g., scikit-learn, gradient boosting, and the tooling behind experiment design). • Strong Python and SQL, • Production ML sensibility: real experience deploying, versioning, and monitoring models (Langfuse, MLflow or similar). You own outcomes after the model ships, including drift and degradation. • Production ML sensibility: • Modern data platform fluency: comfortable working on a lakehouse (Databricks preferred) and partnering closely on the data models your features depend on. • Modern data platform fluency: • AI-Native Mindset • AI-Native Mindset • Hands-on AI tool usage: you already use Claude Code, Cursor, or similar AI development environments as a daily part of how you build. You can speak to where they accelerate your work and where they don't. • Hands-on AI tool usage: • Curiosity about the frontier: you're energized by the pace of AI-driven change—including LLM and agent evaluation—and you bring that energy into the team. • Background in nonprofit, fundraising, or CRM data. • Causal and experimentation work at product scale (experimentation platforms, sequential testing). • LLM and agent evaluation frameworks and techniques. • Familiarity with Data Vault 2.0 or medallion lakehouse modeling.
Responsibilities
• Prove what works, not just what correlates. 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. • Prove what works, not just what correlates. • Build the predictive and forecasting models that drive donor lifetime value, retention, lapse risk, and “will we hit our goal?” forecasting—calibrated, explainable, and honest about uncertainty rather than falsely precise. • Build the predictive and forecasting models • Own model quality and evaluation. Stand up the evals, accuracy bars, and monitoring that keep our AI products and agents trustworthy—because a confident wrong answer costs a fundraiser more than no answer at all. • Own model quality and evaluation. • Get models to production and keep them healthy. Own the ML lifecycle on Databricks and MLflow—training, deployment, versioning, and drift and performance monitoring—so models keep earning trust long after launch. • Get models to production and keep them healthy. • Set the technical direction for data science. Define how we model, measure, and validate; make the call on methods and tooling; and raise the rigor bar through the quality of your own work. • Set the technical direction for data science. • Partner across the stack. Work daily with the data engineers building the data lakehouse, the AI engineers shipping the products. • Partner across the stack. • Use AI tools (Claude Code, Cursor, or similar) daily for analysis, modeling, evaluation, and problem-solving. We expect this to fundamentally change how you work, not just speed up what you'd do anyway. • Use AI tools (Claude Code, Cursor, or similar) daily
Benefits
• Health + WellnessYou’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. • Health + Wellness • Time OffYou'll get a competitive PTO package that includes 20 PTO days, 3 flex days, 4 optional volunteer days, 12 paid holidays, as well as paid parental leave. More is more! • Time Off • 401kYou'll receive a 401k match to help invest in your future. • EquipmentEverything you need to be successful, shipped right to your door. You got this. We got you. • Equipment • Compensation The salary range for this position is $138,100 - $230,200. You may also be eligible for a discretionary bonus. Actual compensation within the range will be dependent on your skills, experience, qualifications, and location, as well as applicable employment laws • LocationThis is a permanent, full-time, fully remote position (within the U.S. and select Canadian Provinces only). Employees living in Indianapolis, IN are welcome to work from our company headquarters. We do not offer Visa sponsorship or relocation assistance at this time. • Location • AccommodationsApplicants who require accommodations may contact [email protected] to request an accommodation in completing an application. • Accommodations
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