GTM Analytics Lead

Spellbook

8d•$129,500 - $162,000•Remote

About The Position

We're looking for a GTM Analytics Lead to help lead the future of growth at Spellbook. You'll define the analytical frameworks and strategic roadmaps behind how our growth team scales customer acquisition across every channel — from paid and organic marketing to product-led growth loops. You'll partner closely with marketing, product, and engineering on experimental design, statistical modeling, implementation, and analysis. Our goal is simple: reach the right lawyer or legal team, with the right message, at the right moment in their buying journey. You'll co-own how we allocate a fast-growing marketing and growth budget.

Requirements

Bachelor's degree or above in Math, Economics, Statistics, Computer Science, Engineering, or another quantitative field, with 5+ years of industry experience as a Data Scientist
Strong Python skills (numpy, pandas, scikit-learn, etc.) across exploratory analysis, predictive modeling, and applied ML for marketing and growth problems
Strong SQL skills (Snowflake, BigQuery, or Redshift preferred)
A track record of shipping measurable improvements alongside growth and product teams, with proven leadership
A strong point of view on the marketing experimentation lifecycle — hypothesis generation, experimental design, statistical analysis, and A/B testing best practices
Deep familiarity with marketing attribution, martech, and the modern privacy landscape
Comfort operating in a fast-paced startup environment where problems are solved through iterative technical solutions

Nice To Haves

Experience at a high-growth startup, ideally in B2B SaaS
Familiarity with enterprise or legal-tech sales cycle metrics
Experience with the modern data stack (Fivetran, Snowflake, dbt, Looker, Hex, or equivalents)
Familiarity with data orchestration tools (Airflow, Dagster, Prefect)
A strong perspective on data science engineering practices — data modeling, version control, testing, and documentation

Responsibilities

Apply statistical, machine learning, and econometric methods to large datasets to evaluate channel performance and isolate the causal impact of marketing and sales activity on a multi-touch B2B sales cycle
Build attribution models and investment frameworks that inform Spellbook's channel spend, helping marketing and finance understand which messages resonate with which segments at each stage of the funnel
Partner with Marketing Ops, Sales, and Engineering to unify data across first- and third-party sources, so every growth decision is made with full context
Drive experimental design across acquisition, activation, and retention surfaces, enabling fast, low-cost iteration on new channels and messaging
Shape the data culture at Spellbook by improving the tools, processes, and systems the broader team uses to make decisions at scale