Lead Casualty Actuary
Lead Casualty Actuary
Woodruff-Sawyer is looking for a highly analytical, skilled, and talented data scientist/actuary with excellent communication skills for the role of Lead Data Scientist. Under the direction of the VP of commercial lines BI, the analyst will perform a wide range of duties involving data collection, data analysis, text mining, presentation building, and related data stewardship activities. The work will also require collaborating with colleagues across property and casualty peers to understand client needs and develop analytical tools and products. A combination of multi-disciplinary skills in loss forecasting, loss development techniques, data science algorithms, and python programming would be essential to be successful in this role. The incumbent should also have ACAS designation and on FCAS track with casualty actuarial society.
- The primary responsibility of the role is to support and execute the casualty analytics and business intelligence agenda of the Woodruff Sayer. The duties involve the following:
- Leads development and automation of loss forecasting capabilities for casualty lines.
- Produces historical loss reserves analysis, loss projections, loss distribution for single and/or multi-line.
- Develops risk evaluation and technical pricing models for casualty insurance.
- Conducting ad-hoc analytical studies, summarizing inputs, and creating dashboards and tools for scalable usage by the non-technical business audience.
- Develops, monitors, and maintains standard industry benchmarks for auto, general liability, and workers compensation lines.
- Gathers, understands, and compiles data from various systems related to property and casualty exposures, retentions, limits, and premiums.
- Develops and writes usage guides for own analytical tools.
- Acts as a data steward and subject matter expert for casualty lines and performs various data stewardship duties related to the team’s work and needs from time to time.
- A Master’s or higher degree in Actuarial Sciences, Mathematics, Finance, Accounting, or similar quantitative disciplines.
- FCAS designation preferable or on track to sit for the exam in 2021/2022.
- Must have 8 or more years of experience in analyzing large casualty risks or reserving analysis.
- Expertise in Python, Excel, SQL, and Tableau.
- Thorough understanding of actuarial and statistical methods involved in building frequency and severity models.
- Excellent communication and presentation skills.