Remote Marketing Data Analyst Jobs
Remote marketing data analyst jobs are open across the U.S. at remote-first companies, distributed marketing teams, and digitally native brands in sectors like e-commerce, SaaS, fintech, and media. Employers hiring remote marketing data analysts right now include Saviynt, Deepgram, and Merative. See the openings below and apply to the ones that match your experience.
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Showing 5 of 11+ Remote Marketing Data Analyst jobs
Location
USA - Remote
Employment Type
Full time
Location Type
Remote
Department
Marketing
Compensation
- San Francisco, NYC & SeattleSan Francisco, NYC & Seattle $120K – $148K • Offers Equity • Offers Bonus
- Everywhere else in the U.S.Everywhere else in the U.S. $115K – $135K • Offers Equity • Offers Bonus
This range is determined by work location and additional factors, including job-related skills and experience. There may be instances where a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.
Please note that the compensation details listed on US role postings reflect the base salary only and does not include bonus, equity or benefits.
Company Overview
Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram.
Company Operating Rhythm
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.
Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. 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.
Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5.
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 email address. If you've received a message claiming to be Deepgram, please forward it to careers@deepgram.com.
Compensation Range: $115K - $148KLocation
USA - Remote
Employment Type
Full time
Location Type
Remote
Department
Marketing
Compensation
- San Francisco, NYC & SeattleSan Francisco, NYC & Seattle $120K – $148K • Offers Equity • Offers Bonus
- Everywhere else in the U.S.Everywhere else in the U.S. $115K – $135K • Offers Equity • Offers Bonus
This range is determined by work location and additional factors, including job-related skills and experience. There may be instances where a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.
Please note that the compensation details listed on US role postings reflect the base salary only and does not include bonus, equity or benefits.
Company Overview
Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram.
Company Operating Rhythm
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.
Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. 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.
Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5.
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 email address. If you've received a message claiming to be Deepgram, please forward it to careers@deepgram.com.
Compensation Range: $115K - $148KSee All 11 Remote Marketing Data Analyst Jobs
Find roles that match your experience and apply in just a few clicks.
Find JobsRemote Marketing Data Analyst Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software
- Consulting & Professional Services
What Employers Look For
The qualifications that appear most often in remote marketing data analyst jobs.
- Proficiency in SQL for querying marketing and campaign performance databases
- Experience with visualization tools such as Tableau, Looker, or Power BI
- Working knowledge of Google Analytics, Adobe Analytics, or similar web analytics platforms
- Ability to design and interpret A/B tests and multivariate experiments
- Bachelor's degree in statistics, mathematics, marketing, or a related analytical field
- Familiarity with marketing attribution models and customer segmentation methodologies
Tips for Your Remote Marketing Data Analyst Job Search
Build a portfolio of marketing analyses
Remote employers want proof you can produce insights without supervision. Publish two or three analyses, like funnel drop-off work, campaign attribution, or cohort retention, using real or public datasets and share them in your application materials so hiring managers can evaluate your thinking directly.
Apply early to remote roles that fit
Migrate Mate lists remote marketing data analyst openings from across the U.S. in one place. Check it regularly, filter for roles that match your skills and seniority, and apply as soon as a relevant opening appears since remote postings attract high application volume quickly.
Demonstrate async communication skills upfront
Remote marketing data analyst teams run on written communication. Use your cover letter and any application materials to show you can explain a complex analysis clearly in writing, because remote hiring managers treat that as direct evidence you'll collaborate effectively across time zones.
Match your skills to remote tool stacks
Remote marketing teams standardize around specific tools like Looker, dbt, Segment, or HubSpot. Read each job posting carefully, identify the stack the team uses, and lead with your experience in those exact tools so your application reads as an immediate fit rather than a training project.
Remote Marketing Data Analyst Jobs: Frequently Asked Questions
How do I get a remote marketing data analyst job?
Target remote-first companies and distributed marketing teams that rely on async workflows, since those employers are most likely to hire marketing data analysts remotely. Remote hiring managers screen hard for self-direction, clear written communication, and hands-on proficiency in tools like SQL, Google Analytics, and Looker or Tableau. A portfolio showing real campaign or funnel analyses gives you a clear edge over candidates who only list skills.
Which companies hire remote marketing data analysts?
Companies hiring remote marketing data analysts right now include Saviynt, Deepgram, and Merative, based on current remote listings on Migrate Mate as of November 2026. Remote-first SaaS companies, e-commerce brands, and digital media firms account for a large share of these openings because their marketing operations are built around distributed teams from the start.
Can you get a remote marketing data analyst job with no experience?
Yes, but remote entry-level roles are harder to land because employers expect you to work independently from day one without in-person guidance. Remote-first startups and digital agencies are the most likely to hire entry-level marketing data analysts. A portfolio of personal or freelance projects that shows campaign analysis, attribution work, or funnel reporting can substitute for formal experience and open doors that a blank resume won't.
Do you need a degree for remote marketing data analyst jobs?
Not always. Remote employers weigh demonstrated skills, tools proficiency, and a portfolio of real analytical work heavily alongside any formal credential. Proficiency in SQL, Google Analytics, marketing attribution platforms, and data visualization tools often carries more weight in a remote hiring decision than the field of a degree, especially at remote-first companies that evaluate candidates through skills assessments or project-based interviews.
Which industries hire the most remote marketing data analysts?
Remote marketing data analyst roles concentrate in Technology & Software and Consulting & Professional Services, based on current remote listings on Migrate Mate as of November 2026. Those sectors hire marketing data analysts remotely because their marketing operations run across distributed teams that depend on shared dashboards, async reporting, and centralized data pipelines rather than on-site collaboration.
See All 11 Remote Marketing Data Analyst Jobs
Find roles that match your experience and apply in just a few clicks.
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