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# Data Scientist: Product

- **Company:** Thatch Corporation
- **Location:** United States (Remote available)
- **Salary:** $160,000 - $230,000
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Business Analytics Applications, Data Analysis, Application Layers, Continuous Integration, Data Transformation, Data Visualization, Database Queries, Github, Python (Programming Language), Machine Learning, Operational Data Store, Ruby on Rails, Microsoft Copilot, SQL Databases, Snowflake, Claude, GPT
- **Published:** October 29, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pvbqsl93sk

## About the Role

* Experience using analytics, data science, and experimentation to influence product decisions.
 * 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 product judgment and the ability to turn complex findings into clear, actionable recommendations.
 * Comfortable working independently, navigating ambiguity, and partnering across teams.

Tools and tech stack

 * Data: Snowflake, SQL, dbt
 * Analytics: Omni, Hex, Python
 * Development: GitHub, CI/CD
 * AI: Claude, ChatGPT, Copilot, and other tools that help us work faster and smarter

You won't work directly in our application layer day-to-day, but familiarity with source data and event instrumentation from systems like Ruby on Rails is helpful.

Experience that stands out

 * Influencing product roadmaps and prioritization through data.
 * Building experimentation practices, including guardrail metrics, sample-size guidance, or analysis frameworks.
 * Analyzing funnels, retention, cohorts, or engagement across complex user journeys.
 * Building statistical or machine-learning models for segmentation, forecasting, propensity, or recommendations.
 * Experience in healthcare, fintech, or other regulated industries.

## Description

* Partner with Product and Operations to answer important questions and inform product priorities.
 * Define and own product metrics, from company-wide success measures to feature-level performance.
 * Analyze user journeys, engagement, and operational data to uncover friction and opportunities.
 * Design and evaluate experiments to measure the impact of product changes.
 * Build and maintain dbt models, metrics, dashboards, and analytical tools that teams rely on.
 * Improve data quality, instrumentation, and self-serve analytics so teams can make confident decisions.