Data Scientist: Growth & Marketing

Thatch•Austin, TX
•$190,000 - $250,000

About The Position

Thatch is seeking a Data Scientist to help its GTM and Marketing teams understand what drives growth and where to invest. The role builds data models and measurement systems for the growth funnel, spanning acquisition, conversion, enrollment, retention, and expansion. The Data Scientist analyzes performance, identifies opportunities, designs experiments, and turns complex data into clear recommendations that inform growth strategy. The position works closely with teams across the business and supports trusted metrics, self-serve analytics, and data quality.

Requirements

  • Experience using analytics, data science, and experimentation to drive growth, marketing, or GTM outcomes.
  • Strong SQL skills and experience with dbt or similar data transformation tools.
  • Experience building analytical data models and dashboards using BI or visualization tools.
  • Proficiency in Python for analysis, experimentation, or statistical modeling.
  • Strong business judgment and the ability to turn complex findings into clear, actionable recommendations.
  • Ability to work independently, navigate ambiguity, and partner across teams.

Nice To Haves

  • Experience with Growth, Marketing, or Revenue Operations analytics, including acquisition, attribution, and lifecycle performance.
  • Experience measuring marketing incrementality through holdouts, geo experiments, lift tests, or similar methods.
  • Experience building statistical or machine-learning models for forecasting, segmentation, lead scoring, or churn.
  • Experience creating tools and automations that help teams make better, faster decisions.
  • Experience in healthcare, fintech, or other regulated industries.

Responsibilities

  • Partner with GTM and Marketing to answer important business questions and guide growth decisions.
  • Analyze acquisition, conversion, retention, and marketing performance to identify opportunities.
  • Own GTM measurement by connecting attribution, CRM, and product data into trusted metrics.
  • Build and maintain dbt models, dashboards, and analytical tools that teams rely on.
  • Design and evaluate experiments to understand what is working and where to invest.
  • Improve data quality and make insights more accessible through self-serve analytics and automation.
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