Staff AI Product Analyst

Angi; United States; On-site; USD 165,000 - 225,000; Full time

Benefits offered by this job

Medical, dental, and vision package

Flexible vacation policy

Pet discount plans

401K with company match

Job summary

Angie's is looking for a Staff AI Product Analyst to define AI-native product analytics. This role will shape the analytical capability, focusing on defining key metrics and ensuring proper evaluation frameworks are in place.

The ideal candidate will have a strong background in product analytics, data science, and systems thinking, and will work closely with AI product and engineering teams to drive organizational outcomes while translating complex insights for business stakeholders.

Qualifications

• 10+ years in product analytics, data science, or technical product management.
• 1+ years of experience with AI/LLM systems.
• Technical proficiency with Python and ML frameworks.
• Proven experience designing AI evaluation frameworks.

Responsibilities

• Define AI-native product analytics and frameworks.
• Partner with AI product and engineering teams.
• Monitor AI analytics workflows and performance metrics.
• Deliver measurement artifacts for leadership.

Skills

Product analytics

Data science

Technical product management

Python

Machine learning frameworks

Data visualization

AI evaluation frameworks

Communication skills

Job description

The Staff AI Product Analyst will define AI-native product analytics for Angi, turning visionary technology into prioritized use cases, robust evaluation disciplines, and a trusted data ecosystem. This role is central to building Angi’s agentic product analytics capability—defining where AI-native analytics creates real leverage, designing the evaluation frameworks that earn organizational trust, and establishing repeatable system standards. As a senior individual contributor, you will have broad influence across the product analytics function and beyond, ensuring that both human teams and AI agents remain aligned on truth, quality, and usefulness.

The ideal candidate is a systems‑thinking data expert who bridges the gap between deep AI capabilities and practical business outcomes.

What you’ll do

• Flagship Journey Measurement: Partner with AI product, engineering, and domain experts to define north‑star and guardrail metrics for flagship AI journeys, focusing on adoption, task completion, quality, and downstream business outcomes.
• Causal Framing & Experimentation: Align closely with data science partners on test design, interpretation, and causal framing when new AI products ship.
• Data Layer Systems Thinking: Map how agents interact with metrics, raw tables, documentation, and APIs to ensure requirements for data and analytics engineering are explicit, structured, and testable.
• Eval Framework Architecture: Design and maintain formal evaluation sets, "golden datasets," rubrics, and regression checks for agent outputs to guarantee accuracy, completeness, policy safety, and usefulness.
• Taxonomy & Failure Mode Analysis: Systematically categorize wrong answers, tool misuse, context gaps, and data edge cases, feeding those insights back into prompts, retrieval (RAG), tools, and data modeling pipelines.
• Performance Monitoring: Monitor live usage of Agentic AI analytics workflows—tracking success, abandonment, fallback patterns, and human override rates to maintain a prioritized engineering improvement backlog.
• Playbooks & Narrative: Own internal documentation defining when to use agents, required human checkpoints, and how to communicate uncertainty. Support enablement and leadership storytelling around agentic AI analytics.
• Strategic Collaboration: Partner with business leaders, the Principal Analytics Engineer, and data engineering teams to translate complex AI capabilities into measurable business outcomes.
• Defining Success: Deliver recurring measurement artifacts (dashboards, reviews, or written readouts) that leadership uses to prioritize roadmaps, while continuously reducing high‑severity incidents where agents produce incorrect metrics.

Who you are

Minimum Qualifications

• 10+ years of experience across product analytics, data science, or technical product management within a complex, high‑scale operating environment.
• 1+ years of direct, hands‑on experience working with AI/LLM systems in an applied context, with a specific focus on evaluating, trusting, and deploying them responsibly.
• Deep technical proficiency with Python, ML frameworks, data visualization/analytics platforms, and standard data management/governance practices.
• Proven track record designing AI evaluation frameworks, including formal evals, golden datasets, production monitoring, or equivalent rigor in a related data discipline.
• Exceptional communication skills with a demonstrated ability to translate highly technical AI insights and tradeoffs into clear narratives for non‑technical business stakeholders.

Preferred Qualifications

• Experience building or evaluating agentic analytics workflows, orchestration frameworks, and familiarity with multi‑agent systems.
• Demonstrated ability to operate fluidly in ambiguity, run structured experiments or pilots, and default to fast action and iteration.
• A systems‑oriented mindset with a healthy skepticism of AI hype, focusing strictly on organizational outcomes and driving technical investments that yield true business value.

The salary band for this position ranges from $165,000 - $225,000, commensurate with experience and performance. Compensation may vary based on factors such as cost of living.

This position will be eligible for a competitive year end performance bonus & equity package.

Full medical, dental, vision package to fit your needs.

Flexible vacation policy; work hard and take time when you need it.

Pet discount plans & retirement plan with company match (401K).

Our hiring process may utilize artificial intelligence (AI) tools to assist in candidate screening and assessment. Our AI tools are designed to complement, not replace, human decision-making.