Applied Science - Research, cMMM
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!
What you’ll do
You will work on research and development of the Haus Causal MMM product. You will be an active contributor to the full product life cycle, collaborating with engineers, product managers, and designers to produce high-quality experiences for our customers.
The ideal candidate will be a hands-on economist/applied scientist with experience in the modern marketing measurement stack (incrementality testing, MMM, MTA) with excitement to both develop new methodologies and directly implement and deploy them via scalable software solutions. You thrive on execution and are able to use strong judgment and clear, succinct communication to drive the right decisions to deliver on our ambitious roadmap.
Responsibilities
Partner with engineering teams to build and deploy causal models into production at scale
Leverage existing literature and develop new science in the causal marketing measurement space
Help drive product roadmap by clearly advocating for rigorous scientific solutions to customer pain points
Qualifications
MSc/PhD in Economics or equivalent industry/academic experience
2+ years working in an Economist / Data Scientist / Applied Scientist role building science models for production environments
Expert in Python and SQL
Experience in the modern marketing measurement stack (incrementality testing, MMM, MTA)
Experience in causal inference and machine learning
Experience coding and troubleshooting models built for deployment
About you
Aim high - you seek to expand on the existing scientific literature by developing novel methods of answering core customer questions
Experiment boldly - you try new approaches and iterate quickly on new scientific hypotheses
Done is better than perfect - you take small exploratory steps rather than large precise leaps toward solutions.
Act like an owner - you share responsibility with the team and do what you can to achieve success. You thrive in ambiguity and find ways to structure unstructured problems.
What we offer
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:
Flexible PTO - take time when you need it!
Equity – Startup environment with part-ownership in our successes
Top of the line health, dental, and vision insurance - multiple plan options so you can pick what fits you best
WFH stipend to support the set up you need to be productive
Events & Offsites – opportunities to connect and celebrate in real life!
Free Lunch – Grab a bite on us when you choose to work from the office (hub locations include SF, NYC and Seattle)
New Parent Leave – take time to welcome your newest Hausmate
We are remote-friendly however candidates based in commutable distance (50 mi?) to SF, Seattle and NYC will be prioritized as we value frequent in-person collaboration opportunities at Haus.
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.