Head of Marketing Data and Measurement

About the role

The Head of Marketing Data & Measurement will build and lead the data infrastructure, analytics practice, and measurement framework that powers every marketing decision at ID.me. This role sits at the intersection of marketing strategy, data engineering, and business intelligence — owning the systems, models, and reporting that connect marketing investment to business outcomes across consumer, enterprise, and government verticals.

Responsibilities

• Design the data architecture from scratch, hire a small team of analysts and engineers, partner deeply with Data Engineering and RevOps, and become the CMO's most trusted source of truth on what is working and what is not.
• 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.
• 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.
• Own the attribution workflow, 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 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.
• 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.
• 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.

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.