Marketing Analytics Manager

ABOUT BASETEN

Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, Open Evidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting‑edge models into production. We're growing quickly and recently raised our $1.5B Series F, led by Altimeter Capital, Conviction Partners, and Spark Capital.

Join us and help build the platform engineers turn to ship AI products.

We're hiring a Marketing Analytics Manager to establish how Marketing at Baseten makes decisions with data. Marketing at Baseten is scaling fast: more spend, more campaigns, more model launches and more inbound. This is a foundational, hands‑on role and the first dedicated Marketing Analytics hire. You'll work directly with Demand Gen, Field Marketing, MOps and Product Marketing alongside GTM, Finance, Product and Engineering to stitch together activities and outcomes across the funnel.

You'll build the data models that connect acquisition, engagement, activation, product usage and revenue. You’ll design dashboards, tools, semantic layers and plugins that enable teams to answer questions. Along the way, you’ll develop an understanding of how customers use Baseten and with this, define how our systems and product can improve.

• Define how Marketing success is measured: establish metrics across audience growth, acquisition, activation, engagement, usage, pipeline and revenue.
• Build the marketing data foundation: ingest and model data across Salesforce, Hub Spot, Google Analytics, advertising platforms, web, email, product and third‑party sources.
• Create a medallion architecture that connects the prospect and customer journeys across systems, from first touch through signup, onboarding, activation and expansion.
• Understand our audiences: develop audience and segmentation frameworks based on customer attributes, intent, engagement and product behavior.
• Own lifecycle marketing analytics: measure performance across web, email, in product and other lifecycle touchpoints. Identify opportunities to improve the journey from acquisition and signup through onboarding and growth.
• Measure awareness and channel impact: establish practical frameworks for understanding brand, awareness and channel effectiveness using audience signals, engagement and downstream product behavior.
• Improve marketing activation and optimization: connect high‑quality conversion and customer signals back into platforms such as Google Ads and Linked In, including offline conversions.
• Architect the building blocks that turn data into action: design and implement A/B experiments, incrementality testing and multi‑touch attribution.

• 5+ years of experience in marketing analytics, growth analytics, product analytics, data science, or another quantitative role, ideally supporting B2B, developer-focused, API, or usage‑based products.
• Deep SQL fluency and strong analytical skills, with a track record of working with large, event‑level datasets and turning ambiguous business questions into decision‑ready analysis.
• Ability to connect data across marketing, CRM, web, SEO/AEO and product systems to understand customer journeys.
• Experience with paid ad platforms such as Google, Linked In and X; how to measure performance and optimize.
• Hands‑on with GTM and marketing systems such as Salesforce, Hub Spot, and Google Analytics.
• Experience building data pipelines and models with a modern data stack such as Airbyte, Fivetran, dbt, Big Query and/or Databricks.
• Comfort working with APIs, automation and integration tools such as n8n or Zapier.

• Experience with AI/ML products and familiarity with inference and training metrics, including how technical product usage can inform customer lifecycle measurement and customer value.
• Experience with usage‑based products, developer platforms or APIs.
• Experience developing multi‑touch attribution, incrementality measurement, media mix models or other approaches for understanding Marketing's contribution across a complex customer…