About the role
from listingSr. Data Analyst
Location: Remote in the United States (ET/CT) | Travel: Occasional travel to NYC or Atlanta
Employees: 50 | Industry: SaaS, Hospitality, Media, Marketing | Reports To: Vice President, Product
Responsibilities
Tracking how often, how favorably, and how accurately clients appear in AI answers versus a defined competitive set - with rigorous baselines, sampling, and stated uncertainty so real change can be distinguished from noise.
Maintaining the tracked-prompt panels (across engines, topics, markets) this runs on, and report movement over time as the core output.
Identifying which sources AI systems cite for a given topic and characterize that mix
Tracking whether and how published content later surfaces as cited evidence, how long that takes, and how long it lasts - surfacing where a client's evidence base is thin and what's missing
Testing which content traits (source, framing, format, specificity, recency, structure) make material more likely to get picked up by AI systems.
Connecting AI visibility to real outcomes — referral traffic, engagement, bookings/conversions and build an honest instrumentation view of what's measurable today, what isn't, and where the recommendation-to-revenue chain breaks
Evaluating AI answers for accuracy, relevance, and completeness; catalog failure modes by engine over time; maintaining the rubrics/benchmarks/rater-agreement process
Continuously refining how prompts are constructed - applying the same evaluation discipline to any AI features built internally
Staying ahead of how AI search systems retrieve/cite sources, validating claims via research (not industry commentary), defining product metrics with product/engineering, ensuring every customer-facing figure is fully re-derivable from documented inputs
Requirements
5+ years of experience in analytics, data science, research, and/or search products
2+ years of experience with AI search, SEO/GEO/AEO, content performance, or LLM evaluation
Hands-on fluency with LLMs + agentic tooling – prompt design, evaluation harnesses, agents that collect and process data at volume
Strong SQL and Python skills – experience with Databricks is preferred (or similar tools)
Proven experience in experiment design applied to observational data – comparison group construction, difference-in-differences or matched comparison, and honest treatment of statistical power
Strong analytical judgement with unstructured text: designing rubrics, coding qualitative signals into structured data, and reasoning carefully about ambiguous cases
Startup experience is required – fast-moving, small teams, high visibility/ownership
Benefits
401K with 4% match, monthly wellness stipend, comprehensive medical and dental insurance plans, long-term disability, and more
Compensation
$120K - $140K + Equity + Annual Bonus
Seniority level: Mid-Senior level
Employment type: Full-time
Industries: Staffing and Recruiting