Responsibilities

• Serve as DRI for measurement product initiatives end-to-end scoping, building, shipping, driving adoption across Marketing and Sales
• Architect and maintain the data modeling layer for marketing measurement clean, tested, documented models that the whole team builds on
• Productize measurement outputs into dashboards, automated reports, and analysis agents that stakeholders use without analyst intervention
• Push insights into end-user tools (CDPs, marketing platforms, CRM) so measurement drives action at the point of decision
• Partner with the pod's technical lead on methodology; translate attribution and incrementality science into production-grade data assets
• Define and enforce modeling standards (naming, testing, documentation) that scale across pods
• Collaborate with Data Engineering on pipeline reliability, orchestration, and upstream data quality
• Report regularly to executive stakeholders, surfacing measurement results with clear next steps

Requirements

• 8+ years of experience in analytics, data science, or marketing measurement
• Experience pulling insight from raw data and shipping durable models and products
• Experience with systems thinking, including how channels interact, where data flows break, and which upstream changes cascade downstream
• Experience writing sophisticated SQL, including well-architected models and clearly documented transformations
• Experience building structured data layers in Snowflake and dbt (or equivalent), including semantic/metrics definitions that keep reporting consistent across tools
• Experience with marketing measurement concepts (attribution, incrementality, media mix)
• Experience with advanced SQL and Python (or R); production experience with dbt, Airflow, or similar
• Experience with a BI platform (Tableau, Looker, Hex, or equivalent)

Preferred

• Experience in B2B SaaS
• Ability to ship early and iterate working assets over polished decks
• Ability to see fragmented data sources as an opportunity to build something coherent the business relies on
• Ability to exercise sharp judgment about what to measure and when "good enough" is the right call
• Multi-touch attribution, media mix modeling, or incrementality testing at scale
• CDPs (ActionIQ, Segment) and marketing platforms (Marketo, Salesforce)
• Causal inference methods geo experiments, synthetic control, difference-in-differences
• MS or PhD in a quantitative discipline (Statistics, Economics, Computer Science)

Benefits

• Paid Time Off: earned time off, as well as paid company holidays based on region
• Paid Parental Leave: take up to six months off with your child after birth, adoption or foster care placement
• Full Health Benefits Plans: options for 100% employer paid and minimum employee contribution health plans from day one of employment
• Retirement Plans: select retirement and pension programs with potential for employer contributions
• Learning and Development: options for coaching, online courses and education reimbursements
• Compassionate Care Leave: paid time off following the loss of a loved one and other life-changing events