Principal Data Analyst

Role overview

Measurement strategy and attribution

• Own measurement across organic, paid, owned, brand, LLM/AEO, media/creators, and earned channels.
• Develop full-funnel attribution across channels and buyer touchpoints, moving beyond last-click to view-based, multi-touch, and buying-group-aware models.
• Create executive-ready reporting that connects marketing investment to revenue outcomes.

Modeling, testing, and forecasting

• Build marketing mix models to quantify marginal channel ROI and inform scenario planning and capital allocation.
• Scale incrementality testing through holdout methods and causal experiments, translating findings into investment recommendations.
• Build predictive LTV models and multi-horizon revenue forecasts connecting marketing signals to downstream revenue and expected ARR.

Leadership and tools

• Partner with Marketing and Finance leadership on evidence-based investment planning.
• Drive build-versus-buy decisions for predictive tooling, including vendor evaluation and external partnerships.
• Lead data science execution and advance AI and machine learning applications across measurement, attribution, targeting, and forecasting.

Required qualifications

• 10+ years in marketing analytics or marketing data science.
• Deep understanding of marketing strategy and its development and execution.
• Hands-on expertise in marketing mix modeling and incrementality testing, connected to capital allocation.
• Experience with predictive LTV models, multi-horizon revenue forecasting, and multi-touch attribution for B2B SaaS buyer journeys.
• Track record building Finance partnerships and shared measurement frameworks that inform budget decisions.
• Technical fluency in experiment design, data science validation, and directing execution teams.
• Experience with view-based and buying-group-level measurement across paid, owned, and earned channels.

Workplace

• Remote role in the United States.

Compensation

• Salary range is USD 152,200–243,500 per year.