Marketing Analyst

GC AI•San Mateo, CA

About The Position

The Marketing Analyst is a key player in GC.AI’s growth engine. You’ll translate marketing data into actionable insights that directly impact pipeline, revenue, and go-to-market strategy. The role requires both analytical rigor and storytelling — bringing clarity to what’s working, what’s not, and what to do next. You’ll work cross-functionally with demand gen, product marketing, sales, and engineering, and you’ll have a direct hand in shaping how the company measures growth, optimizes the funnel, and positions itself in the fast-emerging legal AI category. Why This Role Matters Legal teams today are drowning in work. Our platform changes that, but only if we build it right. As a Design Engineer, you'll be crafting the visual systems and interactions that make sophisticated legal work feel simple and intuitive. Your work won't just look good - it will fundamentally change how legal teams operate, making their work faster, smarter, and more impactful.

Requirements

2–4+ years of marketing analytics experience, preferably in SaaS. Familiarity with B2B AI or legal tech markets a plus.
Strong understanding of marketing funnel metrics, attribution models, and campaign ROI.
Hands-on expertise with HubSpot, GA4, Looker/Tableau/Power BI.
Working knowledge of relational table structures (joins, aggregations, lookups) to ensure accurate reporting across objects.
Comfort with AI-enabled analytics or predictive modeling preferred.
Excellent data storytelling skills — ability to distill complex findings into actionable insights for stakeholders.

Nice To Haves

Experience working with an early-stage series A start-up company.
Understanding legal tech and AI.

Responsibilities

Build dashboards and reports to track campaign performance across channels (paid media, ABM, email automation, events, web).
Develop attribution models (single- and multi-touch) to measure marketing’s influence on pipeline and revenue.
Analyze funnel health (lead → MQL → SQL → closed-won) and identify optimization opportunities.
Partner with demand gen to surface the most efficient campaigns, channels, and conversion paths.
Use AI/ML-powered analytics to identify predictive insights such as churn risk or next-best-action triggers.
Track feature adoption, product usage, and retention drivers to inform product marketing.
Analyze customer behavior, industry trends, and competitor activity to sharpen GTM strategies.
Refine ICPs, IAPs, and personas using firmographic, behavioral, and engagement data.
Recommend new tools and methods to strengthen reporting, enrichment, and segmentation.
Promote a test-and-learn culture through structured experimentation.