Principal Data Analyst

HubSpot is an AI-powered customer platform that provides software, integrations, and resources to help businesses connect marketing, sales, and service. The Principal Data Analyst will lead the evolution of marketing measurement and investment optimization through attribution, marketing mix modeling, incrementality testing, predictive analytics, and forecasting. The role partners with Marketing, Finance, Data Science, Engineering, and Product to support evidence-based capital allocation and executive decision-making.

Responsibilities:

• Deep understanding of full funnel Marketing strategy and techniques
• Own and evolve the marketing measurement framework across organic, paid, owned, Brand, LLM/AEO, media/creators, and earned channels — establishing a single, consistent view of how marketing investment drives revenue
• Own and develop how marketing tracks full funnel attribution across the buyer journey across all channels and touchpoints
• Modernize attribution methodology — moving beyond last-click toward view-based, multi-touch, and buying-group-aware models that capture the full influence of marketing activity on the path to revenue
• Develop executive-ready reporting and performance narratives that connect marketing investment to revenue outcomes, enabling capital allocation decisions with confidence
• Build and operate Marketing Mix Models that quantify the marginal ROI of investment across channels — enabling evidence-based scenario planning and capital allocation between paid, owned, and earned
• Establish and scale an incrementality testing program — designing holdout methodology, running causal experiments, and translating results into investment recommendations
• Partner with Marketing and Finance leadership to move budget conversations from channel-by-channel negotiation toward joint, evidence-based investment planning
• Build and operationalize predictive LTV models that connect upstream marketing signals to downstream revenue outcomes — enabling spend decisions grounded in expected long-term customer value
• Develop multi-horizon revenue forecasting capabilities that translate real-time marketing indicators into expected ARR outcomes, giving Marketing and Finance a continuously updated view of performance
• Drive the build vs. buy roadmap for predictive tooling — evaluating vendor solutions, managing external partnerships, and defining where proprietary models create lasting advantage
• Lead and direct data science execution toward measurement priorities — maintaining the technical depth to design experiments, validate methodology, and hold quality bar on outputs
• Advance AI and machine learning applications across measurement, attribution, targeting, and forecasting to improve the speed and accuracy of marketing decision-making

Requirements:

• 10+ years in marketing analytics or marketing data science
• Deep understanding of Marketing strategy and how it's developed and executed on to inform and build build the right measurement approach behind it
• Deep expertise in Marketing Mix Modeling and incrementality testing — hands-on experience building or operationalizing these capabilities and connecting outputs to capital allocation decisions
• Experience building predictive LTV models and multi-horizon revenue forecasting — connecting leading marketing indicators to expected downstream revenue outcomes
• Experience building or implementing multi-touch attribution models to measure impact across a B2B SaaS buyer's journey
• Track record of building a trusted Finance partnership — developing shared measurement frameworks that drive budget decisions, not just reporting
• Strong technical fluency — able to design experiments, validate data science outputs, and direct execution teams effectively
• Experience with modern, multi-touch attribution approaches across paid, owned, and earned channels, including view-based and buying-group-level measurement
• Excellent executive communication skills — able to translate complex causal findings into clear investment recommendations for non-technical stakeholders
• Marketing measurement and leadership experience at a B2B SaaS or high-growth technology company
• Data science background
• Experience with Brand and LLM/AEO/GEO measurement techniques and attribution
• Background in or close partnership with paid media strategy and bidding optimization
• Experience evaluating and managing external measurement vendors — MMM platforms, incrementality tools, or LTV providers
• Familiarity with B2B buying-group measurement across complex, multi-stakeholder sales cycles