AI Search Analyst

What You’ll Do

• Build and maintain analyses, dashboards, and reporting that track AI search performance, including visibility, citations, competitive movement, prompt/topic performance, and content coverage.
• Translate platform data into clear customer-facing insights and recommendations tied to business goals, customer journeys, personas, and content priorities.
• Partner with Customer Success on client working sessions, reviews, investigations, and strategic readouts.
• Diagnose performance changes by analyzing prompt patterns, topic mix, source behavior, competitor activity, and platform shifts across AI surfaces.
• Design and support measurement frameworks and experiments, including hypothesis development, KPI definition, pre/post analysis, and readouts.
• Conduct quantitative deep dives into questions like what drives citations, where visibility is being won or lost, and how content or technical changes affect outcomes.
• Help improve internal methodologies for trend reporting, benchmarking, segmentation, and performance interpretation in noisy, fast-changing environments.
• Partner with Product and Engineering to surface customer pain points, edge cases, and opportunities for better reporting, analytics, and workflows.
• Contribute to external-facing analysis where useful, including research summaries, benchmark studies, and thought leadership content.

What You’ll Bring

• 2–4 years of experience in analytics, data science, consulting, or a similarly quantitative role.
• Strong foundations in statistics, analysis, and measurement.
• Experience working with messy, high-volume behavioral or product data and turning it into usable insights.
• Strong SQL and proficiency in Python for analysis.
• Experience building dashboards, analyses, or data products that inform decisions for customers or business stakeholders.
• Ability to structure ambiguous problems, choose sensible metrics, and explain what you found, why it matters, and how confident you are.
• Comfort working with noisy, incomplete, or non-representative data, including bias checks, caveats, and uncertainty-aware interpretation.
• Strong communication skills and comfort in customer-facing settings: you can present findings, answer questions live, and adapt technical detail to the audience.

Preferred / Nice to Have

• Experience in digital analytics, SEO, search, content strategy, marketing analytics, or experimentation.
• Familiarity with AI search / LLM platforms and how visibility differs from traditional search.
• Experience with competitive analysis, benchmarking, or performance reporting.
• Exposure to NLP or classification workflows, even if you were not the primary model builder.
• Experience supporting enterprise customers in a strategic, analytical, or solutions-oriented role.
• Familiarity with the web as a system, including content structure, domains, crawlability, and measurement constraints.
• Familiarity with schema.org, structured content, technical SEO, or content operations.

Tools & Tech

• Languages: SQL, Python
• Data: BigQuery, ClickHouse, Postgres, dbt
• Analytics: dashboards, notebooks, experimentation, reporting workflows

Benefits for full-time US employees

• Ownership: Equity in a fast-growing, category-defining company
• Wellbeing: Medical, dental, vision, and life & disability insurance
• Family support: Paid parental leave
• Setup: Home office stipend
• Remote support: Phone and internet reimbursement
• Growth: L&D budget for courses, conferences
• Time off: Flexible PTO
• Financial wellness: 401(k)
• Connection: Team offsites