Staff Product Analyst

Ancestry

3d•$174,720 - $218,400•Hybrid

About The Position

The Product Analytics team helps shape product strategy through rigorous analysis, deep customer understanding, and clear measurement. We define the metrics that matter, identify friction across the user journey, and develop analytical approaches that support product growth and innovation. As a Staff-level Individual Contributor, you will be a technical leader and partner across the organization. You will help set the analytical vision, influence product direction, and raise the bar for the analytics community. You will also play a key role in identifying, creating, and scaling AI-enabled workflows that improve analytical efficiency while maintaining high standards for accuracy, rigor, and business impact.

Requirements

Staff-Level Product Analytics - Experience 8+ years of experience in Product Analytics, Data Science, Growth Analytics, or a related field, with a strong track record of delivering impact at a Staff, Principal, Lead, or equivalent level.
Advanced Technical Expertise - Expert proficiency with the modern analytics stack, including SQL, Python or R, and BI tools such as Tableau. Experience with complex, high-volume behavioral datasets is essential.
AI Fluency and Practical Application - Experience leveraging AI tools, LLMs, automation, or AI-assisted to improve the speed, quality, and scalability of analytical work. You know how to use AI responsibly by validating outputs, managing risk, protecting sensitive data, and ensuring recommendations remain grounded in evidence.
Strong Analytical Judgment - Deep experience selecting the right analytical methods, experimentation frameworks, and measurement approaches for ambiguous business and product problems. You balance methodological rigor with practical business speed.
Influence Without Authority - Exceptional communication skills and the ability to translate complex analysis into clear, actionable recommendations. You partner effectively with Engineers, advise senior Product leaders, and discuss methodology with Analytics subject matter experts.
A Multiplier Mindset - You measure success not only by your own analytical output, but by how much you improve the effectiveness, judgment, and technical capability of the analysts around you.

Responsibilities

Lead Product Measurement Strategy - Own KPI frameworks, metric definitions, and metric trees that help Product teams measure long-term user value, retention, engagement loops, and overall business health.
Generate Proactive Insights - Beyond immediate roadmap questions to explore complex datasets, identify non-obvious user behaviors, and quantify their impact on customers and the business.
Shape Product Strategy with Data - Synthesize multiple data sources into clear, evidence-based points of view on major product opportunities, risks, and trade-offs. Present recommendations directly to senior Product leaders and influence roadmap decisions.
Design Scalable Data Foundations - Partner with Data Engineering and Product teams to improve upstream data models, event tracking, and analytical infrastructure so the organization can support accurate, scalable, and advanced analysis.
Leverage AI to Improve Analytical Efficiency - Identify and implement practical AI use cases that accelerate analytics workflows, including insight generation, data exploration, documentation, code development, quality checks, dashboard creation, and narrative synthesis. Ensure AI-enabled outputs meet high standards for accuracy, explainability, privacy, and analytical rigor.
Create Reusable AI-Enabled Analytics Solutions - Build and share reusable prompts, workflows, templates, automation patterns, and AI-assisted tools that help analysts work faster while improving consistency and quality across deliverables.
Elevate the Analytics Community - Mentor intermediate and senior analysts across the organization by improving technical craft, analytical rigor, code quality, data storytelling, and effective use of AI tools. Help build a high-trust, high-standards data culture.