Responsibilities

• 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.

Requirements

• 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 such as geo testing.
• Proficient in SQL and Python for data analysis, diagnosis, and validation, this is a hands-on-the-data role, not just a strategy role.
• Experience translating ambiguous or messy data problems into clear findings and fixes.
• Track record of presenting analytical results to non-technical stakeholders, including senior leaders, in a way that builds trust rather than confusion.
• Excellent command of English (written and spoken).

Preferred

• Experience with experimental design and statistical inference (power analysis, confidence intervals, causal inference basics) strongly preferred.