Data Product Analyst

🕒 April 21

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Ryz Labs

WebsiteLinkedInAll Job Openings

11 - 50 employees

Ryz Labs builds startups from the ground-up and helps other startups scale by providing top-tier technical talent solutions.

📋 Description

• Partner with Product Managers and Engineers during roadmap and sprint planning to identify high-impact experimentation opportunities • Own the full experimentation lifecycle, including hypothesis framing, test design, instrumentation validation, analysis, and stakeholder communication • Analyze user funnels and retention metrics to identify drop-offs, engagement drivers, and long-term user behavior patterns • Build and maintain dashboards and reporting frameworks to provide visibility into product performance • Investigate anomalies and unexpected changes in metrics, identifying root causes and communicating findings effectively • Conduct ad hoc deep-dive analyses to support product decisions and strategic initiatives • Work directly with event-level product data to uncover insights beyond standard dashboards • Contribute to improving data quality, tracking, and analytical best practices across the team

🎯 Requirements

• 4+ years of experience in product analytics, preferably in high-growth or consumer-facing environments • Strong SQL skills, with experience working on large and complex datasets (Snowflake is a plus) • Hands-on experience designing and analyzing A/B tests end-to-end, including hypothesis definition, metric design, and statistical analysis • Experience working with product event data, including event tracking, instrumentation, and validation • Familiarity with analytics tools such as Amplitude, Harness, or similar platforms • Strong understanding of product metrics such as funnels, retention, and user engagement • Excellent communication skills, with the ability to translate data into clear insights for technical and non-technical stakeholders • Strong ownership mindset, with the ability to independently drive analyses from ambiguous questions to actionable conclusions