Company Description
Givebutter is the most-loved nonprofit fundraising and CRM platform, empowering millions of changemakers to raise more, pay less, and give better. Nonprofits use Givebutter to replace multiple tools so they can launch fundraisers and events, use donation forms and donor management (CRM), send emails and text blasts—all in one place. Use of the Givebutter platform is completely free with a 100% transparent tip-or-fee model.
Givebutter has been certified as a Great Place to Work® in 2021, 2022, 2023, and 2024, and is the #1 rated nonprofit software company on G2 across multiple categories.
Our mission is to empower the changemaker in all of us. We believe giving should be fun, so you’ll want to do it again, and we also believe that work should be fun, so that you’ll have the greatest impact. We are excited to hear from talented people who want to work with other talented people in making the world a butter place—and have fun along the way.
Role Description
As a Data Scientist on the Revenue Team, you’ll be our go-to expert on the customer journey—from first touch through retention—and the data behind it. You’ll leverage your deep statistical and machine learning expertise to understand and optimize every stage of the funnel, working closely with marketing, sales, and customer success to drive revenue growth.
You’ll own the development and execution of sophisticated models and analyses that help us identify opportunities, reduce churn, personalize engagement, and ultimately grow Givebutter’s customer base.
We Want To Hear From People Who…
Responsibilities
SALES, SUCCESS, AND MARKETING ANALYTICS
ACQUISITION, CONVERSION, ENGAGEMENT, AND RETENTION MODELING
Be the subject matter expert on the customer funnel, leading the charge in deepening the company’s understanding of what drives acquisition, conversion, engagement, and retention through behavioral insights.
Develop and maintain models for:
Customer lifetime value
Multi-touch attribution
Customer segmentation and clustering
Churn risk prediction
Engagement scoring
Revenue forecasting
Apply statistical and machine learning methodologies including:
Logistic and linear regression
Clustering and dimensionality reduction
Predictive modeling (e.g., decision trees, random forests, gradient boosting, neural networks)
Causal inference and experimentation (e.g., A/B testing, uplift modeling)
Design and deploy machine learning models that enhance targeting, personalization, and lifecycle marketing efforts.
Collaborate cross-functionally with GTM teams (Marketing, Sales, Customer Success) to embed insights and models into decision-making processes.
Communicate complex findings clearly and effectively to both technical and non-technical stakeholders.
REVENUE DATA MODELING
Requirements
5+ years of experience as a Data Scientist or similar role, ideally within a growth, revenue, or marketing analytics function.
Strong statistical foundations and hands-on experience with:
Logistic/linear regression, clustering, and segmentation
Machine learning techniques (e.g., classification, regression, ensemble methods)
Time series forecasting and anomaly detection
Causal inference and experimentation design
Building and validating predictive models at scale
Expert proficiency in SQL and at least one statistical programming language (e.g., Python, R), and familiarity with machine learning libraries such as scikit-learn, XGBoost, TensorFlow, or similar.
Experience with BI tools (e.g., Looker, Mode, Tableau) and modern data stack environments (e.g., dbt, Snowflake, BigQuery).
A strong business acumen with a deep curiosity about how data can drive decisions.
Excellent communication and storytelling skills—you make data come alive.
Benefits
Hi potential new butterslice! A recent study from LinkedIn _showed that most women apply to jobs only when they meet 100% of the requirements, whereas men will hit the apply button if they hit 60%. Givebutter is committed to building a diverse and inclusive team. So to the women and nonbinary folks out there feeling unsure if you're a perfect fit, we strongly encourage you to apply!_Compensation Range: $160K - $180K
Our world-class support, like our products, is completely free.
Phone, chat, email, social. A real human is here to help you.