As a Marketing Measurement Specialist, you will lead customer engagements in Marketing Mix Modeling, manage data onboarding, and translate model findings into actionable insights for clients.
About Haus
Haus is a marketing science platform that helps brands measure and maximize the business impact of their marketing spend with scientific precision. Over $360B 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 re-allocate it to maximize growth.
Haus was built by a team of former product managers, economists, and engineers from Google, Netflix, Meta, and others to make high-quality decision science accessible to businesses of all sizes. By automating the heavy lifting of experiment design, data processing, and insights generation, we empower our customers to make more profitable, data-driven decisions. We hear our customers frequently rave about our product, for example "we've seen north of 10x ROI on our annual investment in Haus in the first 2 months alone.”
Haus is on a hypergrowth trajectory, 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 and has made the list for 2025's exceptional startups!
The Opportunity
For years, advertisers have lived through the challenges of traditional MMMs: the slow, opaque, and correlational models that are tough to bet on. That's why we're building Causal MMM, the MMM we've forever wished we had. Grounded in incrementality as THE source of truth, and engineered to be served at scale to hundreds of brands. This is your opportunity to be at the forefront of bringing it to advertisers.
What you'll do
As the second MMM Specialist at Haus, you will play a crucial, hands-on role supporting our emerging Marketing Mix Modeling product and ensuring the success of our early customers.
You will be responsible for the end-to-end customer journey, assisting with everything from data onboarding to model interpretation and action planning. Working directly with our scientists and product teams, you will act as a key voice of the customer, helping to drive our product roadmap and deliver an exceptional experience. This is a fantastic opportunity to apply your MMM expertise in a fast-paced startup environment, with a significant long-term opportunity to grow with us as we expand our measurement platform offerings.
Please note, while this role is remote-friendly, we do have offices in NYC, San Francisco, and Seattle that offer a hybrid working option.
Roles & Responsibilities
- Initially lead multiple customer engagements end-to-end, from data onboarding to model interpretation, supporting clients to use our app, preparation of client-facing materials and action planning (i.e. translating cMMM results to planning improvements)
- Build the processes, playbooks, and workflows that will eventually enable Haus' Measurement Strategy Team to take over as MMM customers' primary point of contact and serve our customers with a truly integrated suite of growth intelligence products
- Manage complex data onboarding from intake to validation, working closely with customers and internal teams to ensure all datasets—no matter how messy—are thoroughly vetted and formatted for seamless ingestion into the Haus model, proactively troubleshooting and resolving anomalies as they arise
- Support model iterations: Assist in gathering customer requirements and feedback to support the MMM model design and iteration process, liaising with the Haus data science team
- Explain technical concepts like multicollinearity, uncertainty, and causality to customers to help drive value through understanding MMM features and limitations
- Fuel the flywheel of insights between our incrementality testing solution and Haus' MMM; a flywheel of better, more insightful tests, fueling a more valuable MMM
- Feedback Loop: Gather and relay customer feedback to our product, science, and engineering teams to contribute to the development of scalable product features
- Contribute to building scaled cMMM support by informing and implementing a long-term strategy to support customers as a part of our scalable software roadmap
Qualifications
- Experience with MMM: 3+ years direct experience with Marketing Mix Modeling. You're eager to apply your expertise in MMM to Haus' unique causal and scalable approach to MMM
- Experience with incrementality testing or other marketing experimentation. You understand and appreciate the importance of using incrementality experiments to validate and enhance MMM findings. You also have a general understanding of the marketing measurement landscape
- Customer centricity: 3+ years experience in a customer-facing role. Scrappy and resourceful, and willing to fill any gaps necessary to keep our customers happy. Direct experience at an ad agency is a major plus. We value your firsthand ability to navigate messy media data and translate complex models into the actionable campaign decisions our clients face daily
- Comfortable with ambiguity: you have a track record in navigating the uncertainties that come with product development in ambiguous, early-stage environments by juggling multiple projects and proactively turning uncertainty into an opportunity to solve problems and build from the ground up
- Experience capturing and communicating product feedback from customers to internal technical teams, as well as participating in prioritization and roadmap management decisions
- Growth mindset: You're excited about the longer-term opportunity to grow beyond MMM and contribute to a broader measurement platform
Haus is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law.
Top Skills
Data Processing
Incrementality Testing
Marketing Mix Modeling
Similar Jobs
eCommerce • Food • Information Technology • Mobile • Cybersecurity • App development • Big Data Analytics
Manage key restaurant technology initiatives, ensuring adoption of solutions, developing processes, and leading cross-functional IT initiatives.
Top Skills:
AgileClarizenDeliveryDigital TransformationE-CommerceMobile AppsPosSelf-Order KioskSmartsheet
Consumer Web • Healthtech • Professional Services • Social Impact • Software
The Manager of Security Engineering will oversee application and product security strategies, lead a security engineering team, and integrate secure practices across Headway's services while collaborating with various teams to enhance security.
Top Skills:
Auth0AWSCloudflareDatadogExpelFastapiGitKafkaOktaPython 3React/RemixSemgrepSqlalchemyTeleportTypescriptWiz
Aerospace • Artificial Intelligence • Computer Vision • Software • Analytics • Defense • Big Data Analytics
As an Imagery Analyst, you'll validate geospatial data annotations, conduct quality assurance, and support AI/ML workflows with EO and SAR imagery.
Top Skills:
ArcgisJupyterPythonQgis
What you need to know about the Charlotte Tech Scene
Ranked among the hottest tech cities in 2024 by CompTIA, Charlotte is quickly cementing its place as a major U.S. tech hub. Home to more than 90,000 tech workers, the city’s ecosystem is primed for continued growth, fueled by billions in annual funding from heavyweights like Microsoft and RevTech Labs, which has created thousands of fintech jobs and made the city a go-to for tech pros looking for their next big opportunity.
Key Facts About Charlotte Tech
- Number of Tech Workers: 90,859; 6.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lowe’s, Bank of America, TIAA, Microsoft, Honeywell
- Key Industries: Fintech, artificial intelligence, cybersecurity, cloud computing, e-commerce
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (CED)
- Notable Investors: Microsoft, Google, Falfurrias Management Partners, RevTech Labs Foundation
- Research Centers and Universities: University of North Carolina at Charlotte, Northeastern University, North Carolina Research Campus
