Senior Reserving Actuary: Data-Driven Reserve Analytics Lead

Canopius; New York (NY); On-site; USD 150,000 - 200,000; Full time

Job summary

Canopius in New York, NY is seeking an experienced actuary to own the technical reserves process across multiple lines of business. You will perform quarterly reserve analyses, ensure data quality and the accuracy of inputs, calculations and outputs, and highlight uncertainties and limitations for stakeholders.

The role requires ACAS with FCAS preferred or near completion, strong data skills, and proficiency with Excel, SQL and Python to handle large datasets; you will collaborate with

Qualifications

• ACAS is required; FCAS preferred or near completion.
• Experience in P&C reserving across multiple lines of business.
• Ability to analyze large datasets and communicate uncertainties clearly.

Responsibilities

• Carry out quarterly technical reserves analysis for multiple lines of business.
• Ensure data inputs, calculations and outputs are accurate and highlight limitations.
• Reconcile data across systems and reports to ensure reliability of reserving inputs.
• Communicate results and uncertainties to technical and non-technical audiences for governance and ad-hoc analyses.
• Prepare supporting documents for quarterly and annual reserving governance meetings.
• Support Finance with reserve-related analyses and reporting.
• Mentor actuarial colleagues and contribute to process improvements.

Skills

Actuarial analysis

Data modeling

Communication to non-technical

Team collaboration

Education

ACAS

FCAS preferred

Tools

SQL

Python

Excel

Job description

Canopius in New York, NY is seeking an experienced actuary to own the technical reserves process across multiple lines of business. You will perform quarterly reserve analyses, ensure data quality and the accuracy of inputs, calculations and outputs, and highlight uncertainties and limitations for stakeholders.

The role requires ACAS with FCAS preferred or near completion, strong data skills, and proficiency with Excel, SQL and Python to handle large datasets; you will collaborate with