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Angi

Staff AI Product Analyst

Angi is hiring a Staff AI Product Analyst for a remote role open to applicants in United States. It pays $165k-$225k a year and Level rates it ; you can apply on Angi.

Level's read on this job

  • Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
  • This is listed as a remote role.
  • The posting mentions RAG, AI agents and AI evaluation among its tools and skills.
  • Level classes it as a lead role.
  • Angi has 18 other open roles on Level.

AI in this role

Define AI-native product analytics, evaluation frameworks, and metric systems for agentic workflows and AI journeys.

ragai-agentsai-evaluationai-productproduct-analyticsai-product-strategyevaluation-frameworkscausal-inferenceexperimentation

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.

#LI-Remote

How we rate this

Staff AI Product Analyst at Angi rates 70 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGAI agentsAI EvaluationAI ProductProduct AnalyticsAI Product StrategyEvaluation FrameworksCausal Inference

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How do you decide when an AI agent can act on its own versus asking for approval first?
  3. How do you decide that one model's output is better than another's for a given task?
  4. How do you decide which parts of a product should use AI versus a fixed set of rules?
  5. Tell me about a project where product analytics was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: RAG, AI agents, AI Evaluation, AI Product, and Product Analytics. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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