Jobs at Northbeam

Lead large, complex B2B SaaS product initiatives from concept to launch, owning roadmap, specs, UAT, and go-to-market enablement. Work closely with engineering, data science, and design to embed AI and measurement capabilities (MTA, MMM, incrementality) into product experiences, and engage directly with customers to validate and iterate.

Senior product leader owning company roadmap and driving flagship, data- and AI-driven product initiatives end-to-end. Work directly with customers, partner closely with design, engineering, and data science, manage and elevate senior PMs, run development sprints and UAT, and equip GTM teams. Hands-on player-coach role focused on shipping AI and measurement features for marketing attribution and analytics.

Design and implement scalable backend and distributed systems for a marketing intelligence platform. Build near-real-time ingestion and processing, scale an incrementality/experimentation product, integrate AI-powered workflows, improve data ingestion/exports and connection-state systems, and contribute frontend components to deliver end-to-end product experiences.

Design, develop, and deliver fullstack web solutions, optimize platforms, mentor engineers, and manage product features from ideation to launch.

Lead development and operationalization of measurement products (MMM, incrementality, insights, recommendations). Build, deploy, and maintain production-grade statistical and ML systems, debug end-to-end data and model issues, evaluate methodologies, and partner with engineering, product, and customer teams to improve measurement accuracy and reliability. Provide customer-facing explanations and support for measurement outputs.

Design, build, and maintain scalable data pipelines and tenant-aware APIs to ingest and transform data from varied sources. Work with event-driven and batch architectures, implement authentication and integration patterns, ensure observability/monitoring, optimize data flows for cost and performance, and collaborate with product, infrastructure, and engineering teams to onboard and maintain data sources at scale.