Marketing & GTM Data Analyst

About the role

• Deepgram provides real-time APIs for speech-to-text, text-to-speech, and production-grade voice agents. More than 200,000 developers and 1,300 organizations use its platform, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box.
• Deepgram's voice-native foundation models are available through cloud APIs and self-hosted or on-premises software. Backed by a recent Series C, the company has processed over 50,000 years of audio and transcribed more than 1 trillion words.
• As Deepgram's first Marketing & GTM Data Analyst, you will build the reporting and analytics function within Marketing Operations and identify what is working and where to invest next.
• Partner with the Director of Marketing Operations on the weekly GTM report for leadership, and with Decision Intelligence and Data Engineering on AI analytics agents and the GTM data foundation. Your work will support Marketing, Product, SDR, AE, Partnerships, and RevOps.
• This is a remote role for applicants in the United States.
• Deepgram expects an AI-first mindset. Team members actively use, experiment with, and build advanced AI tools into everyday work. Effective, consistent, and creative AI use is part of how performance is measured.
• Work evolves rapidly. Candidates should be comfortable experimenting, adapting, learning continuously, and adopting new models and workflows rather than expecting highly prescriptive work or a traditional 9-to-5.

Responsibilities

• Automate recurring GTM analytics with Decision Intelligence by designing and improving AI agents for weekly reporting, campaign and sales play readouts, scoring-model checks, and anomaly alerts. Write evaluation cases and quality-check agent outputs as the GTM expert.
• Own Marketing and GTM KPI definitions, calculation logic, and the weekly leadership report, explaining what changed and why.
• Measure marketing campaigns and SDR/AE sales plays from first touch through closed-won. Use pre/post and cohort analysis to recommend what to scale, fix, or stop.
• Create reusable campaign and sales play reporting templates with consistent definitions, time windows, and attribution rules, structured so AI agents can generate first drafts.
• Own Dreamdata and evolve multi-touch attribution, sourcing rules, SDR credit, and partner attribution. Reconcile attribution with Salesforce and HubSpot and translate findings into budget recommendations.
• Evaluate and improve MQL, PQL, and account intent scoring models, including automated monitoring of precision, coverage, and conversion lift by score.
• Define and report partner and business development performance, including partner-sourced and influenced pipeline, co-marketing results, and performance by tier.
• Define GTM source-of-truth datasets with Data Engineering and Decision Intelligence, write the semantic context used by AI analytics agents, and drive upstream data quality fixes.

Requirements

• Turn vague or complex requests into clear, answerable questions before analyzing data, and constructively challenge flawed questions.
• Understand the B2B funnel, including MQL, SAL, SQL, and Closed Won, and how marketing, product-led, partner, SDR, and AE motions interact. Explain the reasons behind the numbers.
• Write strong SQL directly in a warehouse and across Salesforce objects, including Leads, Contacts, Campaigns, Campaign Members, Opportunities, and custom objects.
• Reconcile messy data across systems, maintain high accuracy standards, and fix problems at the source rather than applying downstream patches.
• Have experience owning or improving multi-touch attribution and reconciling it with CRM data.
• Evaluate or tune lead, PQL, or account scoring models and measure their effect on conversion.
• Build AI agents or agentic analytics workflows using tools such as Claude Code, MCP servers, or n8n. Automate recurring analysis and write evaluation cases and context to ensure accurate outputs.
• Build actionable dashboards and recurring reports in a BI tool, with narratives appropriate for leadership.
• Own KPI definitions to ensure metrics mean the same thing across systems and reports.
• Preferred, not required: approximately 3–5 years in marketing analytics, GTM or revenue analytics, or a similar analytical role at a B2B SaaS company, or equivalent demonstrated experience.
• Preferred: hands-on experience with Dreamdata, HockeyStack, Bizible, or a similar attribution tool, plus HubSpot and Salesforce reporting.
• Preferred: Python and experience with dbt, semantic layers, or metric stores.
• Preferred: experience with intent data or partner attribution.
• Preferred: experience at a usage-based, developer-focused, or product-led business.

Company values

• Be You: bring your whole self and a different perspective; diverse viewpoints improve products.
• Be Curious: challenge the status quo, keep learning, and ask how things might be done differently.
• Grow Together: push one another to do great work, welcome feedback, and leave drama out.
• Do the Right Thing: act with integrity and candor, assume best intent, and choose ethics over expediency.
• Think Smart. Act Fast.: weigh high-leverage options, decide, and move without analysis paralysis.
• Put the Customer First: listen with empathy, understand customers' goals, and let their success drive the company's success.

Application information

• Deepgram encourages candidates to apply rather than let the confidence gap or imposter syndrome prevent them from doing so.
• Legitimate Deepgram recruiting communications come from an @deepgram.com email address. Forward suspected impersonation messages to careers@deepgram.com.