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Head of Marketing Data and Measurement

Build and lead marketing data infrastructure, analytics, and measurement frameworks connecting spend to revenue outcomes. Own attribution, dashboards, CDP implementation, and cross-functional data standards.

169k – 236kMountain View, CANew York, NYRevenue OperationsOnsite10+ YOE

About the role

Marketing Measurement & Attribution

  • Design and own ID.me’s end-to-end marketing measurement framework, covering multi-touch attribution, media mix modeling (MMM), incrementality testing, and last-touch and data-driven attribution models across paid, owned, and earned channels.
  • Diagnose and rebuild the broken Salesforce campaign-to-opportunity attribution workflow, partnering with RevOps to establish clean data hygiene, correct field mapping, and reliable pipeline reporting.
  • Build and maintain a unified marketing performance dashboard that gives the CMO and leadership real-time visibility into spend efficiency, channel contribution, and full-funnel conversion across consumer and enterprise motions.
  • Define and operationalize marketing KPIs across all functions including lifecycle, brand, demand gen, events, and partner marketing with consistent definitions, measurement cadences, and executive reporting templates.
  • Lead quarterly and annual marketing performance reviews with data-backed analysis of what drove results, what didn’t, and how to reallocate investment accordingly.

Data Infrastructure & MarTech Integration

  • Own the marketing data stack — including Braze, Salesforce, LinkedIn Campaign Manager, Google Analytics, and any future CDP, BI, or data warehouse tooling — ensuring clean data flows, consistent taxonomy, and reliable event tracking across all platforms.
  • Partner with Data Engineering to build and maintain marketing data pipelines, ensuring campaign events, user behavior signals, and conversion data are captured accurately and available for analysis in the data warehouse (e.g. Snowflake, BigQuery).
  • Lead the evaluation, selection, and implementation of a Customer Data Platform (CDP) to unify ID.me’s 156 million user profiles across marketing, product, and sales touchpoints — enabling identity-driven personalization and segmentation at scale.
  • Define and enforce marketing data governance standards — taxonomy, naming conventions, UTM structure, consent management, and data retention policies — ensuring compliance with privacy regulations relevant to ID.me’s government and healthcare partnerships.

Personalization & Audience Intelligence

  • Build the data foundation for identity-driven personalization — leveraging ID.me’s verified community data (military, veterans, first responders, nurses, teachers, students) to enable segment-specific experiences across web, email, and paid channels.
  • Develop audience segmentation models that combine behavioral, transactional, and verification data to power lifecycle marketing, retargeting, and lookalike acquisition campaigns.
  • Partner with Lifecycle and Growth teams to instrument and measure personalization experiments, establishing a rigorous A/B and multivariate testing practice with proper statistical methodology.
  • Evaluate and recommend personalization infrastructure including CMS integrations (e.g. Contentful + Ninetailed), experimentation platforms (e.g. Optimizely, Statsig), and CDP connectors that unlock segment-level content delivery at scale.

Revenue & Business Impact Reporting

  • Build and own the marketing contribution model that quantifies the revenue impact of brand, lifecycle, demand gen, events, and partner marketing — translating channel metrics into pipeline, revenue influenced, and verified user growth.
  • Partner with Finance on marketing budget planning, scenario modeling, and ROI forecasting — providing the analytical foundation for annual and quarterly budget decisions.
  • Develop event ROI reporting infrastructure from the ground up, connecting lead capture data, Salesforce opportunity data, and actual spend to produce defensible return calculations for every field event.
  • Create and maintain affiliate commission and verification revenue dashboards that give the lifecycle team clear visibility into email channel performance, offer contribution, and community-level monetization.

Cross-Functional Partnership

  • Serve as the primary marketing partner to Data Engineering, RevOps, Finance, and Product Analytics building trusted relationships and shared data standards across organizational boundaries.
  • Act as the internal center of excellence for marketing analytics methodology, tool evaluation, and data literacy running enablement sessions to help non-technical marketers interpret data and self-serve on reporting.
  • Manage relationships with analytics vendors, measurement partners, and agency partners including RFP processes, contract oversight, and ongoing performance management.

Required Qualifications

  • 10+ years of experience in marketing analytics, marketing data engineering, or a closely related field.
  • Deep hands-on expertise in marketing attribution. You have personally built or significantly rebuilt multi-touch attribution models and/or media mix models, and can defend your methodology to a CFO.
  • Strong command of the modern marketing data stack: experience with at least one major CRM (Salesforce preferred), email/lifecycle platform (Braze or similar), paid media platforms, and a cloud data warehouse (Snowflake, BigQuery, or Redshift).
  • Proficiency in SQL; working knowledge of Python or R for analysis and modeling is strongly preferred.
  • Hands-on experience with BI and dashboard tooling (Looker, Tableau, or similar). Established track record of building dashboards that non-technical stakeholders actually use.
  • Experience owning or heavily influencing a CDP implementation or marketing data unification project.
  • Demonstrated ability to translate complex data findings into clear executive narratives and actionable recommendations.
  • Track record of productive cross-functional partnerships with Engineering, Finance, and RevOps teams.
  • Bachelor’s degree in Statistics, Mathematics, Computer Science, Economics, Marketing, or a related quantitative field; advanced degree preferred.

Skills

SQLPythonRSalesforceBrazeSnowflakeBigQueryRedshiftLookerTableauCdpGoogle AnalyticsMedia Mix ModelingMulti-Touch Attribution

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