Data Source Analyst

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

In 2025, Honeycomb was ranked by Newsweek as one of “America’s Greatest Startup Workplaces,” and Calcalist named it as a “Top 50 Israel startup.”

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 18 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.

We are seeking a Data Source Analyst to join our team in enhancing data sources and GIS capabilities across sectors like real estate, insurance, law, and weather. This role focuses on identifying, evaluating, and integrating valuable data sources, collaborating with cross-functional teams, and supporting data-driven decision-making.

What You’ll Do

• Data Sourcing & Acquisition: Identify and assess new data sources through APIs, web scraping, and open datasets. Evaluate feasibility, cost, and ROI.
• Data Manipulation & pre-Integration: Perform data fusion, organizing, and structuring information to maximize usability and insight for stakeholders.
• Supplier Evaluation: Analyze and compare data providers, conducting cost-benefit analyses to select optimal sources.
• Project Management & Reporting: Manage data acquisition projects, document findings, and present insights to stakeholders.
• Cross-functional collaboration: Work with product, sales, and underwriting teams to align data initiatives with business needs.
  
  

• Experience: Mid-level experience in data sourcing or research analysis.
• Technical Skills:
• Familiarity with scripting language (Python or etc) and SQL / noSQL (MongoDB preferred) for data manipulation and querying.
• Familiarity with GIS tools and experience in integrating data layers from multiple sources to enrich analytical capabilities.
• Be able to investigate website structures to determine if data is accessible.
• Analytical & Project Skills: Strong in cost-benefit analysis, information architecture, and Agile methodologies.