angi - Staff AI Product Analyst
Requirements
• 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. • 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. • 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.
Responsibilities
• 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.
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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