Haus Analytics
Haus Analytics builds a causal marketing and incrementality platform for consumer brands to measure ad ROI, run experiments, and optimize budgets using MMM, attribution, and geo testing. It sells enterprise software and services supported by economists and data scientists, serving customers such as Dyson, Wayfair, Sonos, FanDuel, SharkNinja, and Intuit. Founded in 2021 and headquartered in San Francisco, the privately held company raised a Series A in 2023.
Open Positions at Haus Analytics
8 open positions
Build Haus’s Architect product end to end, developing Python backend services and React interfaces that turn marketing measurement into actionable budget recommendations. This backend-leaning full-stack role partners closely with product, science, design, and engineering teams.
Build the backend data platform that automates customer data connection, ingestion, validation, and onboarding at Haus. You’ll work on distributed services, data pipelines, workflows, and APIs that power causal marketing decisions.
Build the data platform workflows and backend services that automate customer data connection, ingestion, validation, and onboarding at Haus. This role combines distributed backend systems, data pipelines, and customer-focused automation at scale.
Haus is hiring a Staff Backend Engineer to build the backend services, ingestion pipelines, and warehouse systems powering its causal marketing platform. The role combines distributed systems engineering with hands-on data platform ownership and technical leadership.
Staff Backend Engineer leading the design of Haus’s backend services and data platform, spanning high-throughput ingestion, distributed systems, and trustworthy BigQuery/dbt models. The role is the senior-most IC on a 6–10 person team and sets technical direction across backend and data engineering.
Staff Machine Learning Engineer leading the development of production machine learning systems for Haus’s causal marketing measurement platform. The role combines probabilistic modeling, causal inference, optimization, and production engineering while mentoring ML engineers and driving cross-functional initiatives.
Lead the development of production machine learning systems for Haus’ causal marketing measurement platform, with a focus on cMMM, optimization, and causal inference. Mentor ML engineers and partner across science, product, and engineering to deliver scalable, trustworthy customer outcomes.
Lead the development of production machine learning systems for Haus’s causal marketing measurement platform, combining optimization, causal inference, and statistical modeling. You’ll guide high-impact ML initiatives, mentor engineers, and help scale trustworthy customer-facing solutions.