Haus is the incrementality platform leading brands trust to optimize billions in ad spend worldwide. Using frontier causal inference-based econometric models to run experiments, we help brands measure the business impact of marketing, pricing, and promotions with scientific precision. Over $360B is spent annually on paid advertising in the US alone, and the famous quote “half the money I spend on advertising is wasted; the trouble is I don't know which half” still rings true. Haus helps marketers identify which half, and reallocate it to maximize growth. With a founding team of former product managers, economists, and engineers from Google, Netflix, Meta, and Amazon, we make high-quality decision science, incrementality testing, and causal marketing mix modeling accessible to businesses of all sizes—automating the heavy lifting of experiment design, data processing, and insights generation. Haus works with leading brands like FanDuel, Sonos, and Dr. Squatch, delivering ROI gains as high as 30x. Haus is well-capitalized and backed by top-tier VCs, including Insight Partners, Baseline Ventures, Haystack, and others. We're honored that Haus has once again been recognized by LinkedIn as a 2025 Top Startup! The Role You’ll build and evolve the systems that power how the world’s leading brands understand the true impact of their marketing spend. Our platform runs geo-based experiments, integrates with major ad platforms (Meta, Google, TikTok), and delivers causal inference results that directly drive budget decisions worth millions of dollars. This is a full stack role where you’ll work across a Python/Flask API, a React frontend, and the data pipelines and integrations that connect them. You'll hit the ground running on a production system with real customers, shipping work that compounds in impact over time. The engineers who thrive here are the ones who can look at a mature codebase, see the path to making it better, and execute without needing to rewrite everything first. We’re also a team that leans into AI-assisted development as a genuine force multiplier — not as a novelty. Our engineers use tools like Claude Code and Cursor to move faster, generate boilerplate, accelerate exploratory work, and ship features that would have taken weeks in days. We’re looking for someone who’s excited about this way of working and wants to push the boundary of what a small, high-output engineering team can deliver.
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Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed