Marketing Measurement Specialist - New York
$160,000–$180,000 year
On-siteNew York, United States
Job Summary
Partner with Measurement Strategy Managers across the cMMM journey, translating model results into concrete planning and budgeting improvements while safeguarding model integrity through QA and update cadence. Own escalations for value realization moments, complex questions, and technical re-engagement, delivering high-quality on-time models that meet SLAs across a sizable book of business. Enable the wider team by defining engagement standards and building playbooks for repeatable cMMM motions, while designing and supervising AI workflows to automate heavy-lift tasks. Act as the analytical co-pilot to the MSM and the voice of the customer to product, science, and engineering, providing structured feedback to shape the roadmap.
Required Qualifications
- 3+ years direct MMM experience (some of the build, full interpretation and recommendation-making)
- experience with incrementality testing or other marketing experimentation
- a general understanding of the measurement landscape
- 3+ years in a customer-facing role
- Scrappy and resourceful
- Comfort in ambiguous, early-stage environments
- experience communicating product feedback to technical teams
- Genuine buy-in to the Causal MMM vision
- belief that MMM can be served at scale
- excitement to help prove the Causal MMM vision
- ability to articulate blockers from experience regarding reservations about the vision
- ideas for busting through blockers
- thinking about how serving cMMM differs from MMM as known
- ideas on how to adjust working style for cMMM
Desired Qualifications
- agency experience
- Value realization beyond model fit
- ideas for designing value realization at Haus
- Scalable approaches to the heavy-lift pieces
- intentionality behind any automation 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
- MTA/MMM articulation
- educating MTA-native clients into MMM
- a view on how MMM, MTA, and experiments fit together in a modern stack
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