Insights Strategist

New York City or San Francisco (Onsite)5+ years

About AirOps

AirOps is the full-service platform for brand growth in the age of AI search. As consumers shift from traditional search engines to platforms like ChatGPT, Claude, and Gemini, the entire ruleset of growth is being rewritten. Buyers now rely on agents to discover, recommend, and purchase products and services for them. If your brand isn't part of the answer, you aren't in the running.

Our platform offers everything a brand needs to get found, recommended, and earn trust. We work with category leaders, including teams at Ramp, Chime, Airbnb, ServiceNow, and Rippling, to drive visibility and accelerate growth from AI search.

Backed by Greylock, Unusual Ventures, Wing VC, and Founder Collective, we're headquartered in San Francisco, New York, and Montevideo.

About the Role

AirOps is hiring an Insights Strategist to analyze AI Search data and turn it into insights that support product decisions and customer guidance. This person will identify the questions worth answering, develop the analysis needed to answer them, and communicate the findings clearly.

The role combines recurring analysis with focused investigation. The Insights Strategist will build ongoing reporting that tracks changes in brand visibility, citations, sentiment, source patterns, and model behavior over time. They will also initiate deeper analyses when the data reveals a material shift or an unexplained result.

This role requires independent judgment about what to analyze and how to translate the results into decisions. The Insights Strategist will work closely with Product and Data to improve AirOps’ metrics, reporting, and product experience. They will also help customer-facing teams apply the findings in conversations with customers and prospects.

What you’ll do

Identify the questions AirOps should be answering with its AI Search data, based on product priorities, customer needs, and changes in the market.
Develop recurring analyses that track AI Search performance across models, topics, brands, and time periods.
Lead focused investigations into changes in visibility, citations, sentiment, source patterns, and model behavior.
Develop and refine the metrics and analytical methods AirOps uses to measure AI Search performance.
Translate findings into recommendations that inform product priorities, customer strategy, and prospect conversations.
Partner with Product and Data to improve the quality, accessibility, and usefulness of AirOps’ data and reporting.
Create clear, customer-ready analyses, presentations, and benchmarks without overstating what the evidence supports.
Present findings to internal teams, customers, and prospects, adapting the level of detail to the audience.
Document analytical methods, assumptions, and limitations so that important analyses can be repeated and trusted.

What we’re looking for

5+ years of experience in insights, analytics, product strategy, data science, consulting, or a related analytical role.
A track record of defining analytical questions and setting priorities, rather than working only from requests created by other teams.
Strong SQL skills and experience working directly with large, complex, or imperfect datasets.
Sound analytical judgment, including the ability to select appropriate methods and distinguish a useful signal from an unsupported conclusion.
Experience building recurring reporting or measurement systems alongside deeper, one-time analyses.
Strong written and verbal communication skills, with the ability to explain technical findings to business and executive audiences.
Experience turning analysis into specific recommendations for product teams, customers, or senior leaders.
Comfort working across Product, Data, Sales, Customer Success, and other functions in a fast-moving environment.

Nice to have

Experience with AI Search, search analytics, SEO, AEO, large language models, or recommendation systems.
Experience analyzing text-heavy or unstructured datasets.
Familiarity with Python, R, notebooks, or business intelligence tools in addition to SQL.
Experience working with B2B SaaS, data products, or analytics platforms.
Customer-facing experience in strategy, consulting, solutions, or insights roles.
Experience developing benchmarks, measurement frameworks, or analytical methodologies used across multiple customers.