About the role
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 As an Implementation Consultant (Internal title: Customer Success Onboarding Manager) at Haus Analytics, you’ll be a dependable, experienced contributor who handles complex onboardings end to end. You’ll take ownership of cMMM onboardings in addition to GeoLift, use Retool and SQL to investigate data issues, and work directly with Product, Data, Science, and Engineering to move fixes forward. You’ll write clear, reusable documentation, strengthen team resources, and exercise judgment in managing priorities across a larger book of concurrent onboardings. You’ll model Haus values through direct communication, steady progress, and thoughtful experimentation. Roles &
Responsibilities: Independently own a full book of onboardings including complex GeoLift accounts (data warehouse connections, custom KPIs, opt-out customers, multi-source setups), self-managing prioritization and flagging risks early Run complex Data Onboarding Calls, proactively identifying data risks during prep (warehouse complexity, custom KPIs, opt-outs) and shaping the call agenda to address them upfront Own cMMM onboardings end-to-end, including non-API spend setup, covariate guidance, and customer education on data