[All remote jobs](https://jobicy.com/jobs.md)[![Deepgram logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2020/12/WRILS-201212160008-406229.jpg)](https://jobicy.com/company/deepgram.md)[Deepgram](https://jobicy.com/company/deepgram.md) # Marketing & GTM Data Analyst AI Summary Deepgram is seeking its first Marketing & GTM Data Analyst to establish scalable reporting and analytics for its go-to-market organization. The role owns KPI definitions, weekly leadership reporting, campaign and sales-play measurement, attribution, and source-of-truth GTM datasets. It requires strong SQL, CRM and marketing-system reconciliation, multi-touch attribution expertise, and the ability to evaluate lead and account scoring models. The analyst will also design and quality-assure AI agent workflows that automate recurring analytics across Marketing, Sales, Partnerships, Product, and RevOps.[Apply for this job](#job-application)[View company](https://jobicy.com/company/deepgram.md)ShareRemote from[USA](https://jobicy.com/job-region/usa.md)SalaryUSD 120k–148k / yrDepartment[Data Science & Analytics](https://jobicy.com/categories/data-science.md)EmploymentFull TimeExperienceDirectorPublished11 Nov 2026Apply before11 Dec 2026Listing views22Application actions1Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. Opportunity details ## About this role. ### Company Overview [Deepgram](https://jobicy.com/company/deepgram.md) is bringing the world’s most natural interface, voice, to the technology we use every day. Our speech models and real-time infrastructure power AI systems that keep up with the way people actually speak. More than 5,000 organizations run conversational voice AI on Deepgram in production, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Cresta, Granola, and Jack in the Box. The Deepgram Voice Agent Platform brings together speech-to-text, text-to-speech and speech-to-speech, with voice-native foundation models available through cloud APIs or self-hosted and on-premises deployments. Built for accuracy, low latency and cost efficiency, Deepgram makes high-quality voice experiences practical to build and run at scale. More than 650,000 developers have used Deepgram to process more than 200,000 years of audio. Every day, more of the world’s conversations with AI run on our models. Operating Principles: Deepgram is a research company that productizes as fast as possible. Four Operating Principles shape how we think, decide, and work together: * Compress before you communicate. You think it through first, then lead with the bottom line. * Resist entropy. You question what already exists before adding more process or tools. * Solve the category. You fix recurring problems at the source, not one case at a time. * Work at the frontier. You go after problems no one has solved yet. We look for people who already work this way, and these principles shape how we grow and evaluate our team. ### AI-First by Default We build AI that millions of people talk to, and we run the company the same way. AI is how we centralize work here, and is core to how we operate. That means more than using the tools. We expect you to: * Build, not just use. Design your own workflows and agents, and use AI to remove whole categories of work instead of doing the same work faster. * Own the output. AI can speed up the work. It doesn’t make anyone less accountable for it. You understand, verify, and stand behind everything you share, including what an agent produces for you. * Spend the time you get back at the frontier. The capacity AI creates goes toward problems no one has solved yet. * Keep pace. Models and tools change every month, and so will your work. You adopt what’s new quickly and drop what no longer earns its place. We judge AI by what it helps you deliver and whether you stand behind the result, not by how often you use it. In interviews, expect to walk us through a workflow you built and where you drew the line between AI and your own judgment. ### Team Overview Marketing Operations keeps Deepgram’s go-to-market engine measurable. As our first Marketing & GTM Data Analyst, you’ll build the reporting and analytics function rather than inherit a finished one, and own the answer to what’s working and where to invest next. You’ll partner with the Director of Marketing Operations on the weekly GTM report leadership reads, and with our Decision Intelligence and Data Engineering teams on AI analytics agents and the GTM data foundation. Your work will power Marketing, Product, SDR, AE, Partnerships, and RevOps. ### Key Goals * 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. ### Minimum Skills, Knowledge & Capabilities * 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. ### Preferred Qualifications (nice-to-have, not required) * 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. ### Our Values * Be You — bring your whole self and a different perspective; diverse viewpoints make our products better. * Be Curious — challenge the status quo, keep learning, and ask ‘how might we?’ instead of accepting limits. * Grow Together — push each other to do great work, treat feedback as a gift, and leave the drama out. * Do the Right Thing — act with integrity and candor, assume best intent, choose ethics over expediency. * Think Smart. Act Fast. — weigh the high-leverage options, decide, and move; no analysis paralysis. * Put the Customer First — listen with empathy, understand their goals, and let their success drive ours. We know the confidence gap and imposter syndrome can get in the way of meeting great candidates — so please don’t hesitate to apply. We’d love to hear from you. Notice: We’re aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @[deepgram.com](http://deepgram.com) email address. If you’ve received a message claiming to be Deepgram, please forward it to careers@deepgram.com. Show more [Apply now >](https://jobicy.com/jobs/161415-marketing-gtm-data-analyst.md) * ![Upload CV](data:image/svg+xml;base64,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) ### Upload your resume now To unlock remote work opportunities and be discovered by global employers. This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 5/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 5/5IndependentCollaborative AI insightThis is a high-ownership founding analytics role spanning complex GTM data, attribution, scoring, and AI automation. Success requires independently defining ambiguous questions, ensuring data quality across systems, and presenting clear investment recommendations to leadership. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Highly competitive$134,000US market range (per year)$115k–$150k0$165k AI insightThe employer discloses a base salary range of $120,000 to $148,000 USD per year, with a midpoint of $134,000. This is a credible annual range for a US-based mid-level to senior GTM analytics role with ownership of attribution, CRM data quality, and AI-enabled reporting. The estimated US market range is $115,000 to $150,000 per year. ## Core skills Skills and capabilities most closely associated with this opportunity. [SQL](https://jobicy.com/jobs?search_keywords=SQL.md)[Marketing analytics](https://jobicy.com/jobs?search_keywords=Marketing%20analytics.md)[GTM analytics](https://jobicy.com/jobs?search_keywords=GTM%20analytics.md)[Multi-touch attribution](https://jobicy.com/jobs?search_keywords=Multi-touch%20attribution.md)[Salesforce](https://jobicy.com/jobs?search_keywords=Salesforce.md)[HubSpot](https://jobicy.com/jobs?search_keywords=HubSpot.md)[Dreamdata](https://jobicy.com/jobs?search_keywords=Dreamdata.md)[Dashboard development](https://jobicy.com/jobs?search_keywords=Dashboard%20development.md)[KPI governance](https://jobicy.com/jobs?search_keywords=KPI%20governance.md)[Cohort analysis](https://jobicy.com/jobs?search_keywords=Cohort%20analysis.md)[Lead scoring](https://jobicy.com/jobs?search_keywords=Lead%20scoring.md)[Data quality management](https://jobicy.com/jobs?search_keywords=Data%20quality%20management.md)[AI agent workflows](https://jobicy.com/jobs?search_keywords=AI%20agent%20workflows.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md) Sample interview questionsHow would you investigate a sudden decline in pipeline while avoiding premature conclusions?I would first define the pipeline metric, time window, segments, and comparison baseline. I would then validate source data across Salesforce, HubSpot, and the warehouse before decomposing the change by source, campaign, segment, stage conversion, sales motion, and cohort. I would present the largest validated drivers, quantify their impact, and identify actions or additional tests. Describe how you would reconcile a multi-touch attribution platform with Salesforce opportunity data. I would document the shared grain, matching keys, attribution windows, opportunity-stage rules, and source definitions before comparing records. I would isolate discrepancies into categories such as missing IDs, timing differences, duplicate contacts, campaign-member gaps, or differing opportunity rules. After agreeing on the authoritative logic with stakeholders, I would implement upstream fixes and establish automated reconciliation checks. How would you evaluate whether an MQL, PQL, or account-intent scoring model is effective? I would assess precision, coverage, calibration, conversion lift, and downstream pipeline or revenue outcomes by score band. I would compare scored cohorts with relevant baselines while controlling for channel, segment, and time period. The result would be a recommendation to adjust thresholds, features, routing, or model definitions based on measurable business impact. What makes a weekly GTM report useful for leadership? A useful report starts with consistent KPI definitions and a concise statement of what changed, why it changed, and what decision is needed. It should separate meaningful signal from normal variation, show key funnel and source breakdowns, and link insights to recommended actions. I would use standardized templates and automated validation so leadership can trust the numbers each week. How would you use AI agents in recurring marketing analytics without reducing analytical rigor? I would use agents for repeatable tasks such as initial data summaries, anomaly detection, report drafting, and quality checks, but define clear inputs, semantic context, evaluation cases, and approval steps. I would test outputs against known scenarios and monitor accuracy over time. Final accountability would remain with the analyst, especially for metric interpretation and investment recommendations. Next step ## Apply now. Follow the employer’s application method and review Jobicy’s safety guidance before sharing personal information. Keep exploring ## Related remote jobs. * ![Particle41 logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2026/11/06a9d08339e9-221.webp) Particle41 Nov 11 New ### [Data Engineer (Tableau)](https://jobicy.com/jobs/161424-data-engineer-tableau.md) Data Engineer Particle41 is seeking a talented Data Engineer to join our team. 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