Role Summary

HIGHLIGHTS

SVP-level actuarial engineering role at a top U.S. insurance brokerage. You will build and operationalize actuarial models across commercial lines and employee benefits, translating complex outputs into client-ready tools and executive presentations. This hands-on, non-people-management role involves Python model development, collaboration with solution engineers on Azure Databricks, and direct engagement with brokers and client executives. Ideal for a credentialed actuary (ACAS/FCAS) with deep commercial lines brokerage or carrier experience.

JOB DESCRIPTION SUMMARY

Design and build actuarial models in Python for D&O, Cyber, GL, PL, Property, and Employee Benefits
Operationalize models on Azure Databricks via structured SDLC with solution engineering partners
Create executive-level presentations and client-facing analytical narratives from model outputs
Hybrid preferred (any U.S. office) or fully remote for qualified candidates
Ideal for FCAS/ACAS with 7+ years commercial lines experience and production-level Python

DOMAIN EXPERTISE

Commercial lines pricing and portfolio analytics
Frequency-severity modelling, loss development, layer pricing
Benchmarking, limit adequacy, and TCOR modelling
Brokerage analytics context (placement/renewal cycles)
Working knowledge of D&O, Cyber, GL, PL, Property, Employee Benefits

KEY REQUIREMENTS

7+ years actuarial experience with 3+ years in commercial-lines brokerage, carrier, or consulting
FCAS or ACAS preferred; credentialed actuary required
Production-level Python for actuarial modeling and statistical analysis
Working knowledge of SDLC, version control, and cloud platforms (Databricks/Azure)
Ability to translate actuarial complexity into clear executive and broker-facing deliverables

TECH STACK

Excel
Power_BI
Azure_Databricks

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Role Summary

HIGHLIGHTS

JOB DESCRIPTION SUMMARY

Design and build actuarial models in Python for D&O, Cyber, GL, PL, Property, and Employee Benefits
Operationalize models on Azure Databricks via structured SDLC with solution engineering partners
Create executive-level presentations and client-facing analytical narratives from model outputs
Hybrid preferred (any U.S. office) or fully remote for qualified candidates
Ideal for FCAS/ACAS with 7+ years commercial lines experience and production-level Python

DOMAIN EXPERTISE

Commercial lines pricing and portfolio analytics
Frequency-severity modelling, loss development, layer pricing
Benchmarking, limit adequacy, and TCOR modelling
Brokerage analytics context (placement/renewal cycles)
Working knowledge of D&O, Cyber, GL, PL, Property, Employee Benefits

KEY REQUIREMENTS

7+ years actuarial experience with 3+ years in commercial-lines brokerage, carrier, or consulting
FCAS or ACAS preferred; credentialed actuary required
Production-level Python for actuarial modeling and statistical analysis
Working knowledge of SDLC, version control, and cloud platforms (Databricks/Azure)
Ability to translate actuarial complexity into clear executive and broker-facing deliverables

TECH STACK

Excel
Power_BI
Azure_Databricks

Role Summary

HIGHLIGHTS

JOB DESCRIPTION SUMMARY

Design and build actuarial models in Python for D&O, Cyber, GL, PL, Property, and Employee Benefits
Operationalize models on Azure Databricks via structured SDLC with solution engineering partners
Create executive-level presentations and client-facing analytical narratives from model outputs
Hybrid preferred (any U.S. office) or fully remote for qualified candidates
Ideal for FCAS/ACAS with 7+ years commercial lines experience and production-level Python

DOMAIN EXPERTISE

Commercial lines pricing and portfolio analytics
Frequency-severity modelling, loss development, layer pricing
Benchmarking, limit adequacy, and TCOR modelling
Brokerage analytics context (placement/renewal cycles)
Working knowledge of D&O, Cyber, GL, PL, Property, Employee Benefits

KEY REQUIREMENTS

7+ years actuarial experience with 3+ years in commercial-lines brokerage, carrier, or consulting
FCAS or ACAS preferred; credentialed actuary required
Production-level Python for actuarial modeling and statistical analysis
Working knowledge of SDLC, version control, and cloud platforms (Databricks/Azure)
Ability to translate actuarial complexity into clear executive and broker-facing deliverables