Measurement Strategy Manager - Enterprise

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 Fan Duel, 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 Linked In as a 2025 Top Startup!

As a Measurement Strategy Lead — Enterprise, you will directly engage a portfolio of large enterprise customers to define and act on their measurement roadmap. You will deeply understand customer business goals, propose testing strategies that align with those goals, and drive action on the insights they gain through Haus. You will serve as an evangelist for incrementality measurement and help your customers make critical business decisions based on Haus reporting.

As a member of a small and rapidly growing team, you will also contribute in ways that benefit the entire organization. Each member of our team brings an area of expertise that elevates the whole.

• Own enterprise client relationships end to end, serving as the primary point of contact for senior stakeholders, including growth leaders, analytics leaders, and data science teams; ensure satisfaction, retention, and expansion across your portfolio.
• Partner closely with client data scientists as day‑to‑day counterparts, aligning on experiment design, data pipelines/requirements, and interpretation standards to accelerate time‑to‑insight and decision‑making.
• Co‑design experimentation roadmaps with customers that reflect their media strategy, operating goals, and test capacity; guide them toward continuous experimentation programs.
• Shepherd the full experimentation lifecycle — from hypothesis and design to implementation, QA, readout, and action planning — translating technical findings into clear, executive‑ready recommendations.
• Advise on measurement methodologies, best practices, and trade‑offs — including MMM calibration and cross‑system alignment — helping customers connect business questions with Haus product capabilities within their broader measurement stack.
• Identify risks early and manage escalations with full ownership, while orchestrating the right internal Haus resources to drive resolution.
• Systematize excellence by creating collateral, playbooks, and workflows that balance quality with scale; contribute to team knowledge‑sharing and coaching.

• 5–8+ years of direct enterprise client management experience in analytics, measurement, or adjacent SaaS/services, with a proven track record influencing senior stakeholders and navigating complex organizations.
• Deep experience with ad effectiveness measurement products and methodology, ideally including incrementality testing and causal inference‑driven approaches (but not required); you can speak fluently about test design, assumptions, and limitations.
• Familiarity with MMM and MTA frameworks — with knowledge of the support structure required to maintain a program involving these tools for an advertiser.
• Hands‑on experience partnering with client‑side data scientists as primary counterparts, including aligning on data specs, QA, modeling/measurement nuances, and result interpretation, knowing you have a full infrastructure behind…