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# Data Scientist 6 - Experimentation Platform

- **Company:** The Ladders
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Python (Programming Language), Standard Sql, Data Streaming, Information Technology
- **Published:** September 5, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pho3ntf2dq

## About the Role

* Advanced degree, such as a PhD or master's, in a quantitative field like Computer Science or Statistics
 * 8+ years of experience in statistics and causal inference specific to experimentation
 * Proven track record of establishing organization-wide standards or tools rather than project-based applications
 * Strong understanding of experimentation challenges and mitigation strategies at a program level
 * Experience translating data science problems into actionable product roadmaps
 * 5+ years of proficiency in data science languages, particularly Python and SQL
 * Exceptional communication skills to influence both technical and non-technical stakeholders
 * A proactive attitude toward learning new methods and optimization techniques

## Description

This role will define the strategic direction for the company's experimentation capabilities, with a strong focus on user experience, data flow, and trustworthy causal measurement. The position will partner closely with data science and engineering teams to shape scalable standards, improve experimentation practices across the organization, and ensure teams have the tools needed to make better product decisions. This is a highly influential role that combines technical rigor, platform thinking, and cross-functional leadership to raise the quality and consistency of experimentation at enterprise scale., * Set the strategic direction for the experimentation platform, focusing on user experience and data flow

 * Ensure the platform uses credible causal inference methods and automate verification processes
 * Collaborate with data science and engineering teams to align product implementation with user needs
 * Shape standards for large-scale experimentation practices across teams
 * Consolidate varied experimentation systems into a streamlined platform with accessible tools and best practices
 * Mentor team members and represent the platform's perspective in broader company discussions


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