Role Summary

HIGHLIGHTS

Senior P&C actuarial/data science role at an insurtech focused on commercial trucking in Orlando, FL. You will own end-to-end reserving (Python-based) and build predictive models using telematics and claims to drive pricing, cancellation strategy, and large-loss detection. The role influences underwriting, dynamic pricing frameworks, and carrier- and agency-level reporting.

JOB DESCRIPTION SUMMARY

Own and enhance Python-based reserving models and end-to-end reserving process
Build and deploy predictive models using telematics, claims, and policy data
Design dynamic pricing frameworks to influence pricing and cancellation performance
Translate data insights into actionable recommendations for underwriting and leadership
Position based in Orlando, FL; US work authorization required (no sponsorship)

DOMAIN EXPERTISE

Actuarial reserving models and insurance forecasting methodologies
Predictive modeling using telematics and claims data
Large-loss modeling and early high-risk claim identification
Designing dynamic pricing frameworks for portfolio management

KEY REQUIREMENTS

Experience with insurance analytics, actuarial reserving, or predictive risk modeling
Strong proficiency in Python for statistical modeling and data analysis
Strong SQL and experience with large-scale, production-grade models
Demonstrated experience with reserving models or insurance forecasting methodologies
Authorized to work for any U.S. employer (no visa sponsorship available)

TECH STACK

No tech stack specified

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Role Summary

HIGHLIGHTS

JOB DESCRIPTION SUMMARY

Own and enhance Python-based reserving models and end-to-end reserving process
Build and deploy predictive models using telematics, claims, and policy data
Design dynamic pricing frameworks to influence pricing and cancellation performance
Translate data insights into actionable recommendations for underwriting and leadership
Position based in Orlando, FL; US work authorization required (no sponsorship)

DOMAIN EXPERTISE

Actuarial reserving models and insurance forecasting methodologies
Predictive modeling using telematics and claims data
Large-loss modeling and early high-risk claim identification
Designing dynamic pricing frameworks for portfolio management

KEY REQUIREMENTS

Experience with insurance analytics, actuarial reserving, or predictive risk modeling
Strong proficiency in Python for statistical modeling and data analysis
Strong SQL and experience with large-scale, production-grade models
Demonstrated experience with reserving models or insurance forecasting methodologies
Authorized to work for any U.S. employer (no visa sponsorship available)

TECH STACK

No tech stack specified

Role Summary

HIGHLIGHTS

JOB DESCRIPTION SUMMARY

Own and enhance Python-based reserving models and end-to-end reserving process
Build and deploy predictive models using telematics, claims, and policy data
Design dynamic pricing frameworks to influence pricing and cancellation performance
Translate data insights into actionable recommendations for underwriting and leadership
Position based in Orlando, FL; US work authorization required (no sponsorship)

DOMAIN EXPERTISE

Actuarial reserving models and insurance forecasting methodologies
Predictive modeling using telematics and claims data
Large-loss modeling and early high-risk claim identification
Designing dynamic pricing frameworks for portfolio management

KEY REQUIREMENTS

Experience with insurance analytics, actuarial reserving, or predictive risk modeling
Strong proficiency in Python for statistical modeling and data analysis
Strong SQL and experience with large-scale, production-grade models
Demonstrated experience with reserving models or insurance forecasting methodologies
Authorized to work for any U.S. employer (no visa sponsorship available)