Job Overview
Location
United States
Job Type
Full-time
Category
Data Science
Date Posted
May 16, 2026
Full Job Description
đź“‹ Description
- • Diagnose performance across the revenue funnel, identify bottlenecks, and recommend data-driven actions to improve velocity, conversion rates, and forecast predictability for Sales, Customer Success, and Marketing functions
- • Lead cross-functional operational initiatives to enhance scalability, efficiency, and rigor across the entire GTM engine, partnering closely with leaders in Sales, Customer Success, and Marketing
- • Define and execute the AI transformation strategy for GTM operations, including automating prospecting workflows, generating intelligent insights, and streamlining Customer Success processes using AI-powered tools
- • Own and evolve the end-to-end GTM tech stack, including Salesforce, HubSpot, Clay, Outreach, and Gong, with a focus on building AI-first automations and workflows that reduce manual effort and increase accuracy
- • Improve data quality and operational reliability by implementing automated audits, data enrichment workflows, and scalable data governance practices across all revenue-related systems
- • Design, optimize, and maintain the company’s enrichment engine and core GTM data infrastructure to ensure consistent, actionable data flows between systems
- • Support and standardize critical operational processes including deal desk workflows, new customer onboarding, and daily GTM execution to ensure alignment across teams
- • Build frameworks, roadmaps, and execution plans to bring structure to ambiguous operational challenges and drive consistent, measurable improvements
- • Collaborate with stakeholders across Sales, Customer Success, Partnerships, and Solutions Architecture to understand end-to-end workflows and align operational systems with business needs
- • Demonstrate a bias for action by moving quickly, learning from iteration, and continuously improving processes without waiting for perfect conditions
- • Communicate effectively with technical and non-technical teams to build trust, gain buy-in, and ensure smooth adoption of new systems and workflows
🎯 Requirements
- • 5+ years of experience in Revenue Operations, Sales Operations, GTM Operations, or GTM Engineering
- • Proven track record managing and optimizing a modern GTM tech stack including CRM, sequencing, enrichment, and analytics tools
- • Experience redesigning business processes and leading cross-functional operational transformation initiatives
- • Demonstrated success identifying, piloting, and scaling AI and automation use cases within business operations
- • Strong understanding of end-to-end GTM workflows across Sales, Customer Success, Partnerships, and Solutions Architecture
- • Ability to bring structure to ambiguity by building frameworks, roadmaps, and execution plans
🏖️ Benefits
- • Health insurance with international coverage, vision, and dental — 100% of team member premium paid
- • Free access to unlimited virtual therapy sessions with licensed human therapists and 24/7 mental health resources
- • Life and Disability Insurance — 100% of team member premium paid
- • $500/month flexible benefit for dependent health insurance or discretionary use (e.g., gym, co-working, travel, food)
- • $1,500 remote work setup fund to equip a productive home workspace
- • Flexible time off with a paid Family Leave policy of 16 weeks for birth or adoptive parents
Skills & Technologies
About Maze Labs, Inc
Maze Labs, Inc. provides a product-discovery and user-research platform for product teams to validate designs and prototypes through quantitative testing and user insights. The SaaS platform lets teams run unmoderated tests, recruit participants, capture task success metrics, and generate reports and analytics to inform design decisions and reduce reliance on qualitative feedback. Maze integrates with design tools and workflows to measure usability, prioritize features, and quantify product-market fit during development. The company serves UX designers, product managers, and researchers at startups and enterprises seeking faster, data-driven validation of product concepts.
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