- Experience
- 2+ yrs
- Salary
- —
- Openings
- 1
- Posted
- 6 days ago
- Work mode
- Work from home
- Eligibility
- Candidates based in the United States who can work aligned with US Eastern or Pacific time zones and who have experience in marketing operations, marketing analytics, or RevOps in a SaaS or digital business context.
- Resume
- Required to apply
Job description
Overview
This is a remote Marketing Operations Analyst role based in the United States, supporting a partner company that will handle all application reviews and hiring steps. The position is central to marketing performance and revenue operations, with responsibility for making sure leads, campaigns, and conversions are tracked accurately across the funnel and tied back to revenue outcomes.
You will help design, maintain, and improve the systems that connect marketing activity with business results, including attribution, lifecycle tracking, automation, reporting, and data quality. The role works closely with RevOps, Marketing, and Sales to keep information consistent across tools such as HubSpot, GA4, CRM platforms, and related systems.
This is a hands-on, high-impact role for someone who is equally comfortable with analytics and marketing operations execution. It offers close exposure to revenue operations and strategic decision-making in a fast-moving SaaS setting.
Key responsibilities
- Take ownership of marketing analytics and tracking setup, including GA4, GTM, Mixpanel, HubSpot, and paid media pixels, to support reliable conversion and behavior measurement.
- Create, improve, and maintain dashboards that show funnel health, campaign ROI, SEO contribution, and paid acquisition efficiency.
- Run HubSpot operations end to end, including workflows, lead routing, segmentation, scoring, and lifecycle automation across the revenue funnel.
- Handle lead data quality by managing enrichment, validation, list cleanup, and syncing across tools such as Clay, HubSpot, and Salesforce.
- Support attribution analysis using first-touch, last-touch, and linear models, and complete manual attribution when required to preserve revenue accuracy.
- Set up and manage A/B tests, including event tracking, data layer configuration, and review of experiment outcomes.
- Keep an eye on website and funnel health, spot unusual patterns or traffic issues, and identify optimization opportunities.
Requirements
- At least 2 years of experience in marketing operations, marketing analytics, or RevOps within a SaaS or digital business environment.
- Practical, hands-on experience with HubSpot, especially workflows, automation, lead handling, and segmentation.
- Strong working knowledge of GA4, Google Tag Manager, and conversion tracking implementation.
- Clear understanding of the B2B SaaS funnel, including MQL, SQL, Opportunity, and Revenue stages, along with lifecycle management.
- Experience using A/B testing tools and working with experimentation methods.
- Good grasp of SEO analytics and how to measure performance.
- Advanced English with strong written and spoken communication skills.
- Ability to work in sync with US Eastern or Pacific time zones.
Benefits
- Fully remote, flexible work setup.
- 20 days of paid time off each year, plus US public holidays.
- Reimbursement support for professional development and upskilling.
- Exposure to a fast-growing SaaS company with strong product-market fit.
- Direct collaboration with leadership across RevOps, Marketing, and Sales.
- Ownership of important marketing systems and revenue data infrastructure.
Additional information
This position is posted on behalf of a partner company, which will manage all applications and next steps. Applications are screened through an AI-assisted matching process designed to review candidates against the role’s key requirements. Shortlisted profiles are then shared with the hiring company, whose internal team makes the final decisions and handles interviews or assessments.
By applying, candidates acknowledge that their personal data may be processed to assess suitability and share relevant details with the employer, based on legitimate interest and pre-contractual measures where applicable. The process may also use AI tools to support tasks such as resume review, response analysis, and inconsistency checks, while final hiring decisions remain human-led.