Actuary/Data Scientist

Berkley•Greenwich, CT

2d•$107,000 - $170,000

About The Position

The Actuary/Data Scientist will use strong analytical and coding skills to support data pipelines and advanced modeling, with an emphasis on rigorous quantitative thinking, high-quality code, and sound professional judgment. The role involves challenging established approaches, applying modern data science and AI methods, and translating complex analyses into clear, actionable insights. The primary location is Greenwich, CT. Sponsorship is not offered for this role.

Requirements

4–7 years of relevant actuarial, technical, or research experience.
Strong programming skills, particularly in Python, including analytical and modeling libraries.
Experience applying AI, machine learning, or LLM-based tools to real data or analytical problems, such as building agents, calling model APIs, or integrating AI into analytical workflows.
Proficiency in probability and statistics.
Experience working with large and complex data flows and articulating project plans and conclusions.
Proficiency with SQL and cloud-based or distributed data environments such as Snowflake or Databricks.
Progress toward CAS credentials (ACAS, nearly or newly FCAS, or international equivalent).

Nice To Haves

Master's degree in Data Science preferred.

Responsibilities

Write production-quality code for data wrangling, modeling, and AI-assisted analytical workflows.
Perform exploratory analysis to identify problems, trends, and drivers.
Use data platforms and pipelines designed by data engineers to develop, enhance, and maintain models, focusing on analytical correctness and model integrity.
Design and apply machine learning tools, including accessing large language models or building task-specific agents.
Validate results using professional skepticism and alternative approaches.
Communicate results to actuarial peers, management, and non-technical audiences.
Understand data types and uses within an insurance organization.
Provide support and guidance to people earlier in their data science or AI journey.