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Job Title: Actuary – Actuarial Analytics / Actuarial Engineering

Actuary – Actuarial Analytics / Actuarial Engineering

Client: Acunor's client

Reporting To: Chief Analytics Officer

Locations: San Ramon, CA, New York City, NY, Summit, NJ, Dallas, TX (Open to other locations)

Work Model: Hybrid, minimum 3 days/week onsite

Compensation: Competitive, based on experience, credentials, skills, and location

Job Overview

Acunor is supporting our client in hiring an experienced Actuary for a hands-on actuarial analytics and actuarial engineering role.

The ideal candidate will combine strong actuarial expertise with modern analytics and technology skills, especially Python, large datasets, and cloud/data platforms. This role reports to the Chief Analytics Officer and focuses on building, validating, and operationalizing actuarial models across commercial lines and benefits, while translating complex outputs into clear business insights for executive and client-facing stakeholders.

Key Responsibilities

• Design, build, and validate actuarial and statistical models for commercial lines pricing, portfolio analytics, benchmarking, and risk analysis.
• Develop actuarial model libraries across areas such as D&O, Cyber, General Liability, Professional Liability, Property, and Employee Benefits.
• Build models related to frequency/severity analysis, loss development, layer pricing, limit adequacy, TCOR, and program benchmarking.
• Translate actuarial outputs into executive-ready presentations, client-facing insights, and business recommendations.
• Partner with data, application, and solution engineering teams to move validated models into scalable analytics solutions.
• Maintain model documentation, validation records, auditability, and quality standards.
• Collaborate with actuarial, business, client-facing, and technical stakeholders to support advisory, placement, and renewal workflows.

Required Qualifications

• 7+ years of actuarial experience.
• 3+ years of experience in commercial lines insurance, brokerage, carrier, or consulting environments.
• FCAS or ACAS preferred; credential flexibility may be considered for strong commercial lines and delivery experience.
• Strong hands-on Python experience for actuarial modeling, statistical analysis, and data manipulation.
• Experience building actuarial models beyond Excel.
• Experience working with large policy, claims, exposure, pricing, benchmarking, or portfolio analytics datasets.
• Familiarity with Databricks, Azure, or similar cloud/data platforms.
• Working knowledge of SDLC concepts such as version control, testing, documentation, and engineering handoff.
• Bachelor's degree in actuarial science, mathematics, statistics, or a related quantitative field; advanced degree preferred.

Preferred Background

• Brokerage analytics experience.
• Strong understanding of how actuarial outputs are used in placement, renewal, pricing, benchmarking, and client advisory discussions.
• Ability to communicate actuarial insights clearly to non-actuarial, executive, and client-facing audiences.
• Experience working with cross-functional teams including actuarial, data engineering, application engineering, business, and client advisory teams.