Data Analyst

Honeycomb

At Honeycomb, we're not just building technology, we’re reshaping the future of insurance.

In 2025, Honeycomb was recognized by Dun & Bradstreet as “Top 10 Best Start Up Companies to Work For” in Israel and named by LinkedIn as “Top 10 Startups in Chicago”.

How did we earn these honors?

Honeycomb is a rapidly growing global startup, generously backed by top-tier investors and powered by an exceptional team of thinkers, builders, and problem-solvers. Dual-headquartered in Chicago and Tel Aviv (R&D center), and with 5 offices across the U.S., we are reinventing the commercial real estate insurance industry, an industry long overdue for disruption. Just as importantly, we ensure every employee feels deeply connected to our mission and one another.

With over $55B in insured assets, Honeycomb operates across 20+ major states, covering 60% of the U.S. population and increasing its coverage.

If you’re looking for a place where innovation is celebrated, culture actually means something, and smart people challenge you to be better every day - Honeycomb might be exactly what you’ve been looking for.

About The Role

Honeycomb runs on data and AI Dashboards, Claude skills, and BigQuery models are production infrastructure that the whole company depends on.

We’re hiring a Data Analyst to make that infrastructure trustworthy, well-instrumented, and increasingly LLM-ready.

This isn’t a “pull data, build dashboards” role. We treat analytics like a product — with clear metric definitions, monitored quality, and consumption layers that serve both humans and AI agents.

What You’ll Do

• Build the business-logic layer. Partner with our data engineer on the gold/semantic layer in BigQuery. Translate business definitions into reusable SQL models that Tableau, Claude skills, and ad-hoc analysis can all trust as a single source of truth.
• Own metric definitions. Become the canonical authority on Honeycomb’s KPIs — bind rate, quote rate, GWP, loss ratio, funnel metrics. Maintain the definitions, their lineage, and the answer to “why do these two dashboards disagree?”
• Build the data infrastructure for LLMs. The differentiated part of this role. Design datasets and Claude skills optimized for natural-language querying, so any stakeholder can ask a free-form question about the business and get a trustworthy answer. Treat the LLM layer as production: versioned, tested, monitored.
• Track feature impact. Embed in the product cycle. Define success metrics before launch, ensure the right data is captured, run the pre/post. No feature ships without a measurement plan.
• Monitor accuracy. Build automated checks for freshness, drift, and metric stability across dashboards and Claude skills. Own the trust level of the analytics surface.
  
  

• 4+ years in analytics, ideally in a fast-moving product environment
• Bachelor’s degree in Industrial Engineering and Management, Information Systems, Economics, or a related field.
• Strong SQL; BigQuery a plus
• Tableau or equivalent, plus the patience to debug definitional inconsistencies
• Git and basic engineering hygiene
• Strong cross-functional communication. Many of our stakeholders - product, underwriting, revenue, leadership - sit in the US while this role is based in Tel Aviv. You’ll need to work fluently across time zones and translate analysis into language that lands with non-technical operators.
• Real curiosity about LLM tooling - you want to be on the frontier of how analytics gets delivered
  
  

• Insurance, fintech, or marketplace experience
• Experience with LLM context/skill files, prompt engineering, or RAG
• Python for data work