Northbeam is a platform for marketing measurement that uses machine learning for DTC and ecommerce brands.
This company offers a hybrid work model combining remote and office work.
Northbeam pioneers marketing measurement with machine learning, empowering DTC and ecommerce brands to understand their true ad spend impact. Our platform gives you a unified view of your business data, helping you track over $25 billion in ad spend and $130 billion in attributed revenue for more than 800 brands globally. We are building the world's most advanced marketing intelligence platform, offering products like Multi-Touch Attribution, Media Mix Modeling (MMM+), and Incrementality. Our technology helps customers accurately track ad spend, understand the full customer journey, and drive profitable growth. You will join a company with strong product-market fit, growing revenue, and deep partnerships with major ad platforms like Meta, Google, and TikTok.
Northbeam is a remote-friendly company, operating with a hybrid model across offices in San Francisco and Los Angeles. You will join a team of driven, collaborative, and talented individuals who value personal growth and excellence. Our culture emphasizes inclusion, curiosity, and respect. We thrive in a fast-paced environment where you can directly shape the industry’s most important measurement challenges. You can expect a high-agency, hands-on approach where deep technical work, cross-functional collaboration, and customer-facing problem-solving are common.
Our Data Science organization forms the intelligence layer of Northbeam, owning the end-to-end science behind marketing measurement and optimization. You will develop and advance core methodologies like Media Mix Modeling (MMM), Incrementality testing, and causal multi-touch attribution (MTA). We craft calibration and validation frameworks and build large-scale experimentation systems. The team focuses on AI-driven insights, recommendations, and creating reusable, scalable, and rigorously validated scientific systems. We translate statistical research and experimentation frameworks into production-ready systems, requiring expertise in Python, SQL, and modern data platforms. You will work on statistical modeling techniques, causal inference, and debug data and modeling issues in production. This involves enhancing the accuracy, robustness, and scalability of existing MMM pipelines. We value strong judgment in selecting, stress-testing, and adapting models to real-world marketing data.