Marketing & GTM Data Analyst

Deepgram is hiring its first Marketing & GTM Data Analyst to build the reporting and analytics function for its go-to-market engine. The role owns KPI definitions, campaign and sales-play measurement, attribution, scoring-model evaluation, and AI-enabled recurring analytics in partnership with Marketing Operations, Decision Intelligence, Data Engineering, and GTM teams.

Responsibilities:

• Automate recurring GTM analytics with Decision Intelligence, designing and improving AI agents for weekly reporting, campaign and sales play readouts, scoring-model checks, and anomaly alerts, as the GTM expert who writes evaluation cases and QAs their output
• Own Marketing and GTM KPI definitions, calculation logic, and the weekly report leadership reads, with a clear narrative on what changed and why
• Measure marketing campaigns and SDR/AE sales plays from first touch through closed-won, using pre/post and cohort analysis to say 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 our attribution practices (multi-touch, sourcing rules, SDR credit, partner attribution), reconcile them with Salesforce and HubSpot, and turn attribution into budget recommendations
• Evaluate and improve MQL, PQL, and account intent scoring models, with 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 AI analytics agents rely on, and drive data quality fixes upstream

Requirements:

• At Deepgram, we expect an AI-first mindset—AI use and comfort aren't optional, they're core to how we operate, innovate, and measure performance
• Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do
• • Turns vague or complex requests ("did re:Invent work?", "why is pipeline soft?") into clear, answerable questions before touching data, and pushes back constructively when the question is wrong
• • Understands the B2B funnel (MQL, SAL, SQL, Closed Won) and how marketing, product-led, partner, SDR, and AE motions interact, and explains why the numbers look the way they do
• • Writes strong SQL directly in a warehouse and across Salesforce objects (Leads, Contacts, Campaigns, Campaign Members, Opportunities, custom objects)
• • Reconciles messy data across systems, holds a high bar for what counts as right, and fixes problems at the source rather than patching downstream
• • Has owned or improved a multi-touch attribution setup and reconciled it with CRM data
• • Evaluates or tunes lead, PQL, or account scoring models and measures whether they improve conversion
• • Operates AI-native: builds AI agents or agentic workflows for analytics (e.g., Claude Code, MCP servers, n8n), automates recurring analysis, and writes the evaluation cases and context agents need to be accurate
• • Builds dashboards and recurring reports in a BI tool that people rely on and act on, with a narrative sized for leadership
• • Owns KPI definitions so the same number means the same thing everywhere
• • Typically ~3–5 years in marketing analytics, GTM or revenue analytics, or a similar analytical role at a B2B SaaS company, or equivalent demonstrated experience
• • Hands-on with Dreamdata, HockeyStack, Bizible, or a similar attribution tool, plus HubSpot and Salesforce reporting
• • Python, and experience with dbt, semantic layers, or metric stores
• • Worked with intent data or partner attribution
• • Experience at a usage-based, developer-focused, or product-led business