The Opportunity:For years, advertisers have lived with traditional MMMs: slow, opaque, correlational models that are tough to bet on. That's why we built Causal MMM - grounded in incrementality as the source of truth, and engineered to be served at scale to hundreds of brands.

We are building a single customer-facing science team - one science org accountable for the customer experience end to end. As a Marketing Measurement Specialist (MSP), you are central to the models for multiple customers. You are the dedicated science point of contact. For other clients, you own escalations, monthly check-ins, on-call support, and model updates. Throughout, you operate as the analytical co-pilot to the MSM (Measurement Strategy Manager), who owns the client relationship.

What you'll do

• Partner with MSMs across the cMMM journey - from kickoff and method presentation through v1 model release, interpretation, in-app enablement, and action planning - translating cMMM results into concrete planning and budgeting improvements across channels and markets, anchored in the customer's business context.
• Safeguard model integrity and update cadence: configure and QA v1 model inputs and outputs, review model updates, and explain method/model/scope changes and multi-KPI insights.
• Own the escalation: value realization moments (business reviews, major planning sessions, handoffs), meaningful method/model/scope changes, complex cMMM questions, custom covariates, and technical re-engagement after customer-team changes - escalating to cMMM Data Science when needed.
• Protect and grow revenue by delivering high-quality, on-time models and follow-ups (deep-dive prototypes, scenario work, before/after narratives, renewal narratives) that help expand accounts, while meeting onboarding and modeling SLAs across a sizable book of business.
• Enable the wider team: define with MSMs what "good MMM engagement" looks like, and build the playbooks, templates, and documentation that let MSMs, Onboarding Managers, and DS run cMMM motions repeatably.
• Bridge manual expertise and automated scale by designing and supervising AI workflows for cMMM - turning your best analyses into guardrails and training data so repeatable tasks are automated safely and you focus on high-value prototypes and complex enterprise challenges.
• Act as a voice of the customer to product, science, and engineering - bringing structured feedback from engagements and partnering on the roadmap - and support case studies, bakeoffs, and pre-sales where your expertise matters most.

Qualifications

• 3+ years direct MMM experience (some of the build, full interpretation and recommendation-making), plus experience with incrementality testing or other marketing experimentation and a general understanding of the measurement landscape.
• 3+ years in a customer-facing role. Scrappy and resourceful; agency experience is a plus. You can navigate messy media data and translate complex models into the actionable campaign decisions clients face daily.
• Comfort in ambiguous, early-stage environments - juggling multiple customers while making progress on longer-term process building - and experience communicating product feedback to technical teams.
• Genuine buy-in to the Causal MMM vision. You believe MMM can be served at scale - frequent updates, incrementality results as direct model inputs - and you're excited to help prove it. If you have reservations, you can articulate the blockers from your experience and ideas for busting through them.
• Already thinking about how serving cMMM differs from MMM as you've known it - the cadence, experiments guiding the model, and operating in support of a client-owning MSM - and how you'd adjust your working style.

Bonus Points

• Value realization beyond model fit - you've made MMM value tangible to clients and have ideas for designing that at Haus.
• Scalable approaches to the heavy-lift pieces - data collection, covariate selection, insights delivery - with intentionality behind any automation you've built.
• A point of view on how an MMM-first incrementality testing roadmap differs from a GeoLift-first one - test sequencing, channel prioritization, experiment design.
• A framework for differing conviction levels across model outputs given uneven experimental coverage by channel, and how that shapes recommendations.
• MTA/MMM articulation - educating MTA-native clients into MMM, and a view on how MMM, MTA, and experiments fit together in a modern stack.

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 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.