Data Scientist I

Verisk | Verisk
Boston, MA

We are seeking a Data Scientist to join our Casualty Catastrophe Model (CCM) team in Boston or Jersey City. In this role, you will help design and deliver analytical models that assess emerging and systemic liability risks, translating complex research into scalable, production‑ready solutions used by global clients.

You will work across the full model lifecycle—from early‑stage mathematical and statistical research to implementation within Verisk products—partnering closely with research peers, software engineers, and product teams. This is a hands‑on, highly collaborative role that blends data science, probabilistic modeling, and applied analytics with real business impact.

If you enjoy solving ambiguous problems, building robust analytical systems, and explaining complex ideas clearly to diverse audiences, this role offers the opportunity to make a meaningful contribution in a growing and mission‑critical modeling space.

What You’ll Do

As a member of the Casualty Catastrophe Model team, you will:

  • Develop and enhance casualty catastrophe models and analytics addressing systemic and emerging liability risks
  • Conduct statistical, mathematical, and data‑driven proof‑of‑concept analyses to inform model design and validation
  • Translate research prototypes into scalable model components for production use
  • Partner closely with product and software teams to implement model methodology into Verisk workflows
  • Build and maintain model development pipelines using Python, SQL, Git, and AWS
  • Analyze data from multiple sources to support model parameterization, testing, and improvement
  • Perform validation, sensitivity testing, and robustness analyses
  • Contribute to clear technical documentation outlining assumptions, methodology, and limitations
  • Support client inquiries by explaining model behavior and results in a practical, accessible way
  • Communicate technical findings to both technical and non‑technical audiences
  • Stay current on advances in data science, modeling, and insurance analytics
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