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# Staff Data Scientist, Data Products

- **Company:** The Ladders
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $180,000.0 - $205,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, R (Programming Language), Python (Programming Language), Mixpanel, SQL Databases, Tableau (Software), Usage Analysis, Data Analytics
- **Published:** September 27, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pmw263vtne

## About the Role

* 8+ years in product analytics, data science, or a related field with software product experience.
 * Proficiency in AI-assisted development tools for enhancing analysis and product development.
 * Familiarity with AI and BI innovations to enhance data products and user experiences.
 * Proven track record leading complex, cross-functional projects with significant impact.
 * Deep expertise in SQL and proficiency in Python, R, or similar languages.
 * Advanced knowledge of statistical methods, data modeling, and analytical validation.
 * Experience designing event schemas and dashboards with BI tools like Mixpanel or Tableau.

## Description

This role will lead product measurement and analytics efforts that shape decisions across data-driven offerings. The position partners closely with engineering and cross-functional stakeholders to define success metrics, strengthen instrumentation, and translate usage patterns into clear business recommendations. It is also responsible for evaluating new data products for analytical soundness, privacy considerations, and overall product health., * Own product measurement strategies to define success metrics and guide decisions.

 * Collaborate with engineering on event instrumentation for user tracking and privacy compliance.
 * Conduct detailed analyses of product adoption and user engagement to derive actionable insights.
 * Create and maintain dashboards for product health visibility for teams and leaders.
 * Translate complex usage data into clear recommendations for stakeholders.
 * Lead analytical strategies for new compensation and workforce data products.
 * Evaluate data products for analytical defensibility and privacy preservation.


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