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Haus is seeking a Software Engineer for their Science Platform in New York. This role involves building and maintaining the platform that powers how leading brands measure the causal impact of their marketing spend. You will work primarily in Python, collaborating with applied scientists and product engineers to translate research into production code and ensure results flow into the customer-facing application. The ideal candidate has 3+ years of experience in production software systems, strong Python proficiency, experience with data-intensive applications, SQL, and cloud-native environments. Experience with workflow orchestration frameworks and AI development tools is a plus.
About Haus
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!
You'll build and maintain the platform that powers how the world's leading brands measure the true causal impact of their marketing spend. Our Science Platform runs geo-based experiments across 100+ customers, processes daily analysis pipelines, and delivers statistical results that directly drive budget decisions worth millions of dollars.
This is a backend and platform engineering role. You'll work primarily in Python across a set of tightly integrated repositories: a statistical estimation library, a science orchestration library, and a Metaflow-based job execution system running on Kubernetes. You'll collaborate closely with applied scientists to translate research into production code, and with product engineers to ensure results flow cleanly into the customer-facing application.
You won't be starting from a blank canvas — you'll be joining a production system that serves real customers and shipping improvements that compound. The engineers who thrive here are the ones who can navigate a complex, multi-repo codebase, understand the science well enough to be a productive partner, and ship reliable systems without needing to rewrite everything first.
We're also a team that leans into AI-assisted development as a genuine force multiplier. Our engineers use tools like Claude Code and Cursor to move faster, 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.
We’re a high-performance, low-ego team operating in a fast-moving environment. We care deeply about our customers and expect everyone to take full ownership of their work — this is a place where high expectations fuel even higher growth.
If you thrive in ambiguity, take pride in raising the bar, and want to work alongside top-tier peers who challenge and support you, you'll find unmatched opportunities here. If you're looking for predictability or rigid structure or you prefer order-taking to go-getting, we’re probably not the right fit — and that’s okay.
We work in small, mission-driven teams that prioritize inclusion, collaboration, and growth over hierarchy or red tape.
Some of our benefits include:
We value in-person collaboration at Haus and give preference to candidates within commuting distance of our offices in San Francisco, Seattle, and New York City.
Haus is an equal opportunity employer. We make hiring decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected status.
We believe diverse perspectives make us stronger and are committed to an inclusive culture where everyone feels seen, heard, and empowered to contribute. Bring your authentic self — we would love to hear from you.