Senior 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