Marketing Measurement Specialist - New York

Posted 6 Days Ago
Be an Early Applicant
New York, NY, USA
In-Office
160K-180K Annually
Mid level
Software
The Role
Own marketing measurement models for multiple customers, from configuration and QA through interpretation, updates, escalations, and action planning. Partner with strategy managers to translate causal MMM results into budgeting and channel decisions, protect revenue through high-quality deliverables, build scalable playbooks, supervise AI workflows, and provide customer feedback to product, science, and engineering teams.
Summary Generated by Built In

About Haus

Haus is the causal marketing platform top businesses trust to optimize billions in ad spend worldwide. With support from PhD economists, data scientists, and growth experts, Haus’ AI-driven technology translates complex marketing measurement into clear action and outcomes, enabling brands like Dyson, Wayfair, Sonos, Fanduel, SharkNinja, and Intuit to optimize spend, accelerate growth, and make smarter marketing decisions at scale.

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.
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.

Skills Required

  • 3+ years of direct Marketing Mix Modeling experience, including model building, interpretation, and recommendations
  • Experience with incrementality testing or other marketing experimentation
  • General understanding of the marketing measurement landscape
  • 3+ years of experience in a customer-facing role
  • Ability to navigate messy media data and translate complex models into actionable campaign decisions
  • Comfort working in ambiguous, early-stage environments while managing multiple customers and process-building initiatives
  • Experience communicating product feedback to technical teams
  • Buy-in to the Causal MMM vision and ability to explain how serving Causal MMM differs from traditional MMM
  • Agency experience
  • Experience making MMM value tangible to clients
  • Experience creating scalable approaches to data collection, covariate selection, or insights delivery
  • Perspective on MMM-first incrementality testing roadmaps versus GeoLift-first roadmaps
  • Framework for evaluating differing conviction levels across model outputs
  • Ability to articulate how MTA, MMM, and experiments fit together in a modern measurement stack

Haus.io Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Haus.io and has not been reviewed or approved by Haus.io.

  • Healthcare Strength Healthcare includes medical, dental, and vision with multiple plan options and is described as “top of the line,” signaling robust core coverage for a startup.
  • Leave & Time Off Breadth Flexible PTO and “all the classics, plus some” holidays indicate generous time‑away norms that support rest and recharge.
  • Equity Value & Accessibility Equity grants are explicitly offered, positioning employees as owners and aligning rewards with company outcomes.

Haus.io Insights

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The Company
HQ: Los Angeles, CA
65 Employees
Year Founded: 2021

What We Do

Haus is a decision science platform built on your own data. Our products combine state-of-the-art causal inference and econometrics to help brands make informed investment decisions.

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