Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale.
The Elastic Search AI Platform is used by more than 50% of the Fortune 500.
Complete, cloud-based solutions for search, security, and observability.
Responsibilities
Meet with business leaders to understand their problems and decisions; turn them into analyses, recommended actions, and clear requirements for systems and data.
Recommend which systems, tools, and products to prioritize, with a clear point of view and reasoning.
Build the business case for each investment: expected value, required resources, and total cost of ownership.
Design the overall architecture for marketing and sales measurement, and build core data models, pipelines, and machine learning datasets.
Build models that show how marketing spend and activity convert to pipeline and revenue, and measure the full customer path from first touch to closed deal.
Define account-based performance measures and apply them with Sales and Marketing.
Combine attribution, incrementality, and mix modeling into one consistent view.
Build tools that let marketers ask questions in plain language and get trusted answers.
Set standards for metric definitions, data quality, and privacy compliance (GDPR/CCPA).
Plan roadmaps and milestones with Data Engineering, Analytics, and IT.
Mentor senior analysts and engineers.
Requirements
Bachelor's degree or equivalent in a quantitative or technical field (Economics, Statistics, Engineering, or Computer Science).
10+ years in marketing or GTM analytics at a B2B company.
Experience designing data and analytics architecture and recommending tools and platforms to build, buy, or retire.
Experience building business cases, including cost, value, and total cost of ownership, and influencing senior leaders.
Consultative style; able to uncover business pain points and turn them into analysis plans.
Funnel economics and performance modeling experience across sales and marketing data.
Experience with account-based strategy, motions, and frameworks, and with marketing lifecycle and deal lifecycle analytics.
Proficient presentation skills to explain methods, trade-offs, and results to executives and non-technical teams.
Extensive SQL and dbt (or similar), data modeling, and cloud data warehouse experience, preferably BigQuery.
Python or R skills, with clean, tested code.
Hands-on experience with attribution, incrementality testing, and/or marketing mix modeling, plus applied statistics.
Knowledge of machine learning models and ability to help build and use them in production.
Experience mentoring and developing others.
Bonus: experience with Salesforce, Marketo, or similar GTM systems data.
Bonus: experience across PLG, SLG, ABM, and Enterprise sales motions.
Bonus: experience building natural language question-and-answer tools for business data.
Bonus: privacy-first and cookieless measurement experience.
Conditions
Base salary only; no variable compensation component.