Marketing & GTM Data Analyst (AI)

Location: Remote within the USA

Base salary: $120,000–$148,000 in San Francisco, New York City, and Seattle; $115,000–$135,000 elsewhere in the U.S. Equity and bonus are also offered.

Company

Deepgram provides real-time voice AI APIs and self-hosted and on-premises software for speech-to-text, text-to-speech, and production voice agents.

What you will do

• Build the marketing and GTM reporting and analytics function and own the weekly leadership report, KPI definitions, calculation logic, and performance narrative.
• Automate recurring GTM analytics by designing, improving, and evaluating AI agents for reporting, campaign and sales-play readouts, scoring-model checks, and anomaly alerts.
• Measure marketing campaigns and SDR/AE sales plays from first touch through closed-won using pre/post and cohort analysis.
• Create reusable campaign and sales-play reporting templates with consistent definitions, time windows, and attribution rules.
• Own Dreamdata attribution and reconcile multi-touch, sourcing, SDR, and partner attribution with Salesforce and HubSpot.
• Define GTM source-of-truth datasets with Data Engineering and Decision Intelligence, improve data quality upstream, and report partner and business development performance.

Requirements

• Approximately 3–5 years of experience in marketing analytics, GTM analytics, revenue analytics, or a similar analytical role at a B2B SaaS company, or equivalent demonstrated experience.
• Strong understanding of the B2B funnel, including MQL, SAL, SQL, and Closed Won, and how marketing, product-led, partner, SDR, and AE motions interact.
• Strong SQL skills in a data warehouse and across Salesforce objects, including Leads, Contacts, Campaigns, Campaign Members, Opportunities, and custom objects.
• Experience owning or improving multi-touch attribution and reconciling it with CRM data.
• Hands-on experience with Dreamdata, HockeyStack, Bizible, or a similar attribution tool, plus HubSpot and Salesforce reporting.
• Experience evaluating or tuning lead, PQL, or account scoring models and measuring precision, coverage, conversion lift, or other improvements.
• Experience with Python and with dbt, semantic layers, or metric stores.
• Experience reconciling messy data across systems, fixing data quality issues at the source, and maintaining consistent KPI definitions.
• Experience building dashboards and recurring reports in a BI tool with a leadership-ready narrative.
• AI-native operating experience, including building AI agents or agentic analytics workflows with tools such as Claude Code, MCP servers, or n8n, and writing evaluation cases and context for accurate outputs.

Nice to have

• Experience with intent data or partner attribution.
• Experience at a usage-based, developer-focused, or product-led business.

Culture & Benefits

• AI use and comfort are core expectations, with active experimentation and integration of advanced AI tools into daily work.
• Fast-moving environment requiring adaptability, continuous learning, experimentation, and independent judgment.
• Values include diverse perspectives, curiosity, feedback, integrity, speed, and customer focus.
• Equity and bonus are offered in addition to base salary.