About this role.
Angi is seeking a Staff AI Product Analyst to establish AI-native product analytics for agentic workflows. The role defines north-star metrics, causal measurement approaches, evaluation frameworks, golden datasets, and production monitoring for AI-generated analytics. This senior individual contributor partners closely with AI product, engineering, analytics engineering, data science, and business leadership. Success depends on converting AI capabilities and failure modes into trusted, measurable business outcomes and prioritized engineering improvements.
Role DNA
A quick view of the complexity, pace, ownership and collaboration implied by the job description.
Job Complexity
5/5Pace & Pressure
4/5Autonomy Level
5/5Communication Load
5/5Salary analysis
Estimated compensation compared with the broader US market for similar roles.
Core skills
Skills and capabilities most closely associated with this opportunity.
Sample interview questions
I would begin with the user decision or workflow the agent is intended to improve, then define a north-star outcome such as validated task completion or time-to-insight. I would pair it with guardrails for accuracy, policy safety, user abandonment, fallback use, human overrides, latency, and downstream business impact. I would establish baselines and instrument the full journey before assessing incremental lift through experiments or carefully framed observational analysis.
I would construct a representative golden dataset covering common requests, high-value workflows, edge cases, ambiguous prompts, and known failure modes. Each case would include expected outputs or scoring rubrics for factual accuracy, completeness, correct tool use, uncertainty communication, and policy compliance. The framework would run pre-release regression tests and be supplemented by production sampling, human review, and severity-based incident tracking.
I separate superficial engagement from validated outcomes. Beyond usage, I measure whether users complete the intended task, whether outputs are accepted or overridden, whether recommendations are accurate, and whether the workflow changes a downstream business metric. I also assess cost, latency, and operational risk so that apparent productivity gains are not offset by errors or expensive human verification.
I would first triage severity, isolate affected users and decisions, and add safeguards or temporarily restrict risky capabilities if necessary. I would classify examples by root cause, such as retrieval gaps, semantic-layer defects, incorrect tool selection, prompt ambiguity, or source-data quality. I would then prioritize fixes with engineering partners, add the cases to regression evaluations, and communicate the issue, uncertainty, mitigation, and recovery criteria clearly to stakeholders.
I would use a concise narrative that states the decision, evidence, confidence level, limitations, and recommended next action. For example, I would distinguish a measured experiment result from directional production signals and quantify known error or override rates. This gives leaders a practical basis for action without overstating the certainty of the AI system or the analysis.
For over 30 years, Angi has powered the future of the home services industry, creating an environment where homeowners and pros benefit from more jobs done well.
For homeowners, our platform is a reliable way to find skilled pros. For pros, we’re a reliable business partner who helps them find the winnable work they want, when they want. For employees, we’re an amazing place to call home. We can’t wait to welcome you.
Angi at a glance:
Founded in 1995 as Angie’s List and rebranded in 2021
Global company with 9 brands in 8 countries and employees worldwide
Homeowners have turned to us for 300 million home projects and counting
About the team
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
AI Product Strategy & Metrics Design
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.
Evaluation, Governance & Backlog Management
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.
Cross-Functional Leadership & Enablement
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
Bachelor’s in computer science or a quantitative field (e.g., Computer Science, Statistics, Mathematics, or related fields).
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.
Compensation & Benefits
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)
The rare opportunity to work with sharp, motivated teammates solving some of the most unique challenges and changing the world
We value diversity
We know that the best ideas come from teams where diverse points of view uncover new solutions to hard problems. We welcome and value individuals who bring diverse life experiences, educational backgrounds, cultures, and work experiences.
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.
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