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Measurement Consultant - Boston

Job in Boston, Suffolk County, Massachusetts, 02298, USA
Listing for: funnel.in.th
Full Time position
Listed on 2026-09-12
Job specializations:
  • IT/Tech
    Data Analyst
Salary/Wage Range or Industry Benchmark: 90000 - 110000 USD Yearly USD 90000.00 110000.00 YEAR
Job Description & How to Apply Below

About the Role

We're looking for a Measurement Consultant to join Funnel's Measurement Solutions team in Boston. This team owns Advanced Marketing Measurement, Attribution, Incrementality Experimentation, and Media Mix Modeling - as a core part of Funnel's product portfolio.

This is a mid-level role for someone who can own client engagements end-to-end: designing the right measurement approach for a client's situation, building and defending the models, and communicating results to stakeholders up to CMO/CFO level. You'll work at the intersection of client consulting and Funnel's product and engineering teams, and you'll be expected to bring a point of view - not just execute a playbook.

What You Will Do
  • Own measurement engagements for a portfolio of clients, MMM, MTA, and incrementality testing from scoping through readout.
  • Advise clients on measurement strategy and operations, including how to structure learning agendas and prioritize what to test next.
  • Build, customize, and validate models in Funnel's self-service MMM and triangulation system, exercising judgment on model selection, outlier handling, and sanity-checking outputs against ground truth.
  • Design and execute experiments (geo holdouts, matched-market tests, lift studies) including power analysis, estimator selection, and results validation.
  • Query and manipulate data directly (SQL, Python) to diagnose data quality issues, reconcile discrepancies, and validate pipeline outputs, you're comfortable getting into the data yourself rather than relying on others.
  • Use AI tools (e.g., Claude, ChatGPT, Copilot, or similar) as a core part of your workflow to write and debug code faster, synthesize client data into narratives, draft client-ready materials, and build internal tools that make the whole team more efficient.
  • Present findings and recommendations to client stakeholders, including senior leadership, translating technical results into clear business narratives and calibrating tone for sensitive or contested findings.
  • Navigate multi-stakeholder client situations (agencies, internal client teams, competing incentives) with sound judgment about what to share, when, and with whom.
  • Act as a bridge between client-facing work and Funnel's product/engineering teams surfacing patterns across clients that should inform the roadmap, not just individual feature requests.
  • Contribute to internal methodology and tooling (playbooks, reusable analysis frameworks, case studies) that raise the bar for the broader team.
  • Stay current on the measurement landscape (new methods, competitor approaches, industry shifts) and use that to sharpen both client recommendations and internal product strategy.
Who You Are

You're a technically capable marketing practitioner who can operate with real autonomy. You understand data generation processes deeply enough to spot when something's wrong before a client does, and you can independently choose and defend a modeling approach rather than just running a standard process. You're equally comfortable in a spreadsheet, a SQL console, and a client meeting. You're AI-forward by default, when you hit a new problem, experimenting with AI tools is one of the first things you try, not a last resort.

Skills and Experience
  • 2-4 years of experience in marketing analytics, marketing execution, or a closely related quantitative field.
  • Demonstrated, hands-on experience using AI tools to accelerate real work e.g., using an LLM to write/debug analysis code, build a lightweight internal tool, speed up client deliverables, or explore a problem you didn't already know how to solve. We'll ask you to talk through a specific example.
  • Strong working knowledge of modern marketing measurement methods (MMM), Attribution, and (quasi-)experimental designs…
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