Bevi is seeking a GTM Data Scientist to accelerate our go-to-market function by measuring the true incremental impact of marketing spend and building churn and expansion models across our customer base. The role sits at the intersection of Marketing and Sales, partnering with Sales, Marketing, and RevOps to translate data into a clear point of view on what to do next. You will build predictive models to identify churn risk, surface upgrade opportunities, and create look-alike prospects; own cohort reporting to track performance over time. You will develop marketing mix models (MMM) and incrementality analyses to quantify marketing ROI across digital and offline channels, including events, BeviMobile, and social, guiding budget optimization decisions. You will identify leading indicators for weekly performance and collaborate with the Marketing Analytics Engineer to ensure data structures are accurate and well understood. You should have 2–4 years of experience in data science, applied statistics, or analytics, with hands-on experience building predictive models (logistic regression, gradient boosting) and familiarity with causal inference or MMM/incrementality methods. Strong SQL and Python/R skills, experience with data visualization tools (Looker, PowerBI, Hex), and a proactive, clear communicator mindset are required. The position is based in Boston, Massachusetts, United States, and is offered on a hybrid basis. Pay range: $120,700—$149,100 USD.

Bevi is seeking a GTM Data Scientist to accelerate our go-to-market function by measuring the true incremental impact of marketing spend and building churn and expansion models across our customer base. The role sits at the intersection of Marketing and Sales, partnering with Sales, Marketing, and RevOps to translate data into a clear point of view on what to do next. You will build predictive models to identify churn risk, surface upgrade opportunities, and create look-alike prospects; own cohort reporting to track performance over time. You will develop marketing mix models (MMM) and incrementality analyses to quantify marketing ROI across digital and offline channels, including events, BeviMobile, and social, guiding budget optimization decisions. You will identify leading indicators for weekly performance and collaborate with the Marketing Analytics Engineer to ensure data structures are accurate and well understood. You should have 2–4 years of experience in data science, applied statistics, or analytics, with hands-on experience building predictive models (logistic regression, gradient boosting) and familiarity with causal inference or MMM/incrementality methods. Strong SQL and Python/R skills, experience with data visualization tools (Looker, PowerBI, Hex), and a proactive, clear communicator mindset are required. The position is based in Boston, Massachusetts, United States, and is offered on a hybrid basis. Pay range: $120,700—$149,100 USD.