Compensation Intelligence Lead (7)

Summary

To support the Global Rewards team, the full-time remote Compensation Intelligence Lead will design and construct data systems, automated pipelines, and AI-powered tools to enhance Quince's compensation strategies, from offers to equity refreshes and market benchmarking.Key responsibilitiesArchitect and build custom tooling that integrates various HR systems into a unified, live data environmentDesign and deploy an automated benchmarking process that includes real-time market data scraping and trend analysisBuild and maintain AI-powered workflows to automate compensation processes and provide actionable insights to stakeholdersRequired qualificationsDemonstrated experience actively building with AI tools, including prompting and scripting with LLMs or AI APIsExperience in compensation, total rewards, or people analytics, or a strong curiosity about compensation mechanismsStrong proficiency in data tools and scripting languages (Python, SQL, or similar) for building automated pipelinesProven ability to work with large datasets and translate findings into clear outputs for non-technical stakeholdersExperience working with HRIS, ATS, or people systems such as Rippling, Greenhouse, or Pave

Job Description

To support the Global Rewards team, the full-time remote Compensation Intelligence Lead will design and construct data systems, automated pipelines, and AI-powered tools to enhance Quince's compensation strategies, from offers to equity refreshes and market benchmarking.Key responsibilitiesArchitect and build custom tooling that integrates various HR systems into a unified, live data environmentDesign and deploy an automated benchmarking process that includes real-time market data scraping and trend analysisBuild and maintain AI-powered workflows to automate compensation processes and provide actionable insights to stakeholdersRequired qualificationsDemonstrated experience actively building with AI tools, including prompting and scripting with LLMs or AI APIsExperience in compensation, total rewards, or people analytics, or a strong curiosity about compensation mechanismsStrong proficiency in data tools and scripting languages (Python, SQL, or similar) for building automated pipelinesProven ability to work with large datasets and translate findings into clear outputs for non-technical stakeholdersExperience working with HRIS, ATS, or people systems such as Rippling, Greenhouse, or Pave