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# Backend Engineer (Ruby), AI Engineering: Agent Observability

- **Company:** Mozilla Corporation
- **Location:** Circle, AK, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Code Review, Information Engineering, Firefox, Python (Programming Language), SQL Databases, Data Analytics
- **Published:** August 9, 2026
- **Apply:** https://www.workingnomads.com/job/go/1779640/

## About the Role

* 8+ years of experience in data science, analytics, or applied quantitative analysis, with a track record of shaping product strategy through data
 * Demonstrated ability to lead complex, cross-functional analytical initiatives from problem framing through stakeholder alignment to decision
 * Deep expertise in experimentation (A/B testing) and causal inference, with strong judgment about when each method applies and what conclusions they support
 * Advanced proficiency in SQL and Python for analysis, modeling, and validation
 * Experience defining and owning product metrics that teams actually use to make decisions
 * Strong opinions, loosely held: you can take a position on what the data says, advocate for it clearly, and update when the evidence changes
 * Track record of mentoring or technically leading other data scientists
 * Commitment to our values:

 * Welcoming differences
 * Being relationship-minded
 * Practicing responsible participation
 * Having grit

## Description

* Own the analytical strategy for a product area: identifying the highest-leverage questions, defining the measurement framework, and ensuring data-driven decisions
 * Serve as a strategic partner to product and engineering leadership, translating ambiguous business problems into analytical approaches and clear, actionable recommendations
 * Define north-star metrics and measurement strategies to set goals, evaluate progress, and make trade-offs
 * Design and oversee experiments and causal analyses, ensuring methodological rigor and that results drive real product decisions
 * Develop and maintain a deep understanding of user growth dynamics: how acquisition, activation, and retention interact to drive growth, and use that understanding to diagnose metric movements, explain trends to leadership, and anticipate emerging risks or opportunities
 * Contribute and own areas of the team's forecasting and growth modeling efforts, helping translate statistical models into actionable growth strategies
 * Mentor and elevate other data scientists through code review, methodology guidance, and establishing reusable analytical frameworks
 * Represent data science in cross-functional forums, making the case for what the data shows even when it challenges prevailing assumptions
 * Drive alignment across data science, data engineering, and product on shared priorities like data quality, metric definitions, and instrumentation


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