Actuarial Analytics Director - Reinsurance

Group 1001   is a consumer-centric, technology-driven family of insurance companies on a mission to deliver outstanding value and operational performance by combining financial strength and stability with deep insurance expertise and a can-do culture. Group1001’s culture emphasizes the importance of collaboration, communication, core business focus, risk management, and striving for outcomes. This goal extends to how we hire and onboard our most valuable assets – our employees.

Why This Role Matters:

This is a hands-on, build-it-yourself position for a quantitative professional who is equally comfortable working in an actuarial reserving triangle and in a production data pipeline. This position owns both the analytics and the data foundation the business runs on, designing, building and operating the insurance and reinsurance data pipeline end to end, then using that foundation to develop the pricing, reserving and capital models that inform real decisions.

The modeling work is genuinely consequential: sophisticated models supporting capital optimization, business growth, reinsurance strategy and risk management, with direct exposure to the leaders who act on them. It is also genuinely hands-on. There is no team of engineers between this role and the data. This role will write the code, validate the numbers, and stand behind the output, and in return get end-to-end ownership of an analytics platform.

This position will work across multiple fronts at once, partnering closely with colleagues in Risk Management, the Guarantee business and the Reinsurance business. Exceptional attention to detail and consistently accurate results are non-negotiable. This role may also supervise analysts, offering a path to build and lead a team as the function grows.

How You'll Contribute:

Actuarial and Quantitative Analysis:

Oversee Portfolio Surveillance, Loss Model, Mark to Market and Capital Adequacy reports.

Oversee loss reserving analysis and methodology across the reinsurance and RVI portfolios.

Oversee Capital Charge Models for all lines of business and the whole company.

Develop scorecards to manage concentration and accumulation risks for the whole company.

Peer review reinsurance transactions.

Reinsurance Data Pipeline and Data Science:

Design, build and own the end-to-end reinsurance data pipeline, covering submission and exposure data from cedent, broker, MGA and fronting partners.

Develop and maintain the reinsurance and treaty database, together with the data structures supporting loss reserving methodologies.

Ensure model inputs are auditable and defensible for auditors, rating agencies and regulators.

Apply statistical and machine learning techniques to insurance data, including claims frequency and severity modeling, fraud and leakage detection, portfolio segmentation and predictive underwriting triage.

Perform exploratory analysis on new lines of business where credible internal data is thin and design the data capture required to build that credibility over time.

Collaboration and Presentation:

Support all new business development for US and international markets, including market research across North American and other developed markets.

Provide any requested quantitative analysis and information for various business lines and corporate initiatives.

What We're Looking For:

• Bachelor’s degree in actuarial science, economics, statistics or related field; advanced degree a plus.
• 7-10 years’ experience in an analytical position, preferably in P&C insurance or reinsurance.
• 2-5 years’ experience of managing a quantitative, actuarial or data team.
• Demonstrated experience building or substantially rebuilding a data pipeline or analytical data platform, rather than solely consuming one.
• Reinsurance, fronting, MGA or program business experience strongly preferred.
• Demonstrates initiative, takes ownership and has strong work ethic.
• Ability to conduct in-depth research on business issues and effectively communicate findings in verbal or written format efficiently.
• Ability to train, manage and mentor small teams.
• Strong interpersonal, leadership and collaboration skills.
• Strong intellectual curiosity with the ability and drive to learn new subjects, tasks and skills quickly; comfortable asking questions and verifying information and requirements.
• Technical Skills: Strong understanding of actuarial principles, reserving and pricing technique, compliance requirements, risk management technique and financial modeling (ACAS or FCAS is a plus).
• Excellent skills and experience in data analyses and data management, including comfort with messy, incomplete and inconsistently formatted real-world insurance data, and the judgment to know when to fix it, flag it or work around it.
• Advanced SQL and Python. Proficient in Microsoft Excel and working knowledge of statistical software such as R, STATA or SAS.
• Strong desire to write the query, clean the file, build the model and ship the report personally. This is a builder’s role, not a purely supervisory one.
• Comfortable operating on multiple fronts at once, shifting between strategic modeling work and detailed data remediation without losing momentum.