Marketing Analyst

Clay Labs•New York, NY

16d•$145,000 - $200,000

About The Position

We’re looking for a Marketing Analyst to be the connective tissue between data models, insight and strategy. In this role, you’ll own the reporting, metrics, and insights that drive clarity on how our marketing efforts are performing. You’ll work in a pod with marketing / sales leadership, analytics engineering, GTM Engineering and strategic finance. You’ll surface deep insights, work with our data teams to build dbt models, and obsesses over what makes Clay’s marketing efforts successful.

Requirements

5+ years of analytics experience, with 3+ years in marketing analytics at a high growth SAAS company
Proven ability to translate data into actions that drive business impact.
Highly proficient in SQL is non negotiable (ideally python too); experience working with large, complex data sets.
Deep understanding of the marketing funnel, from acquisition to retention.
Track record of working cross-functionally with marketing, sales, ops, and analytics engineering teams.
Curiosity and persistence in solving complex problems; adaptability when findings evolve.
Proficiency in BI tooling (Streamlit, Hex, Sigma preferred) with ability to build and own dashboards with compelling visualization
You are AI forward: you can vibe code applications to supplement core tooling, you achieve personal ROI from CLI and agents

Nice To Haves

experience building in Clay

Responsibilities

Own the health of the top-of-funnel "assembly line": monitor lead flow end-to-end, identify where leads are leaking, stalling, or being misrouted, and drive tactical fixes with GTM Engineering and marketing.
Diagnose gaps between intended and actual funnel behavior — campaigns not triggering expected follow-up, routing rules dropping leads, conversion stages behaving off-plan — and quantify the impact of each fix.
Build operational reporting and monitoring (alerts, anomaly detection, funnel diagnostics) that drives day-to-day and week-to-week action, surfacing performance insights for leadership.
Ensure that data models, metric definitions, and funnel stage logic accurately reflect how the business actually operates, partnering with Analytics Engineering to close gaps.
Serve as the connective layer between systems builders (GTM Engineering) and data model owners (Analytics Engineering), translating operational findings into pipeline and model improvements.
Feed ground-truth funnel data and channel diagnostics into the attribution and goaling work led by Strategic Finance and GTM leadership.
Provide actionable insights into campaign and channel performance to influence in-flight decisions, not just quarterly strategy reviews.