The Catastrophe Modeling Analyst is responsible for cleaning clients exposure data to enable accurate modelling of Cat risk (i.e. earthquakes hurricanes floods etc.) as well as that from other manmade exposures such as Terrorism. The major tasks include data cleansing and modelling data from insurance clients in third party software (AIR) through an excel API.
- Cleansing Address and other location level information (scrubbing importing and geocoding data).
- Liaise with Underwriters on specific account requests.
- Understand and extract information from Insurance contracts (slips).
- Analyze modeling data from insurance clients in third party software such as AIR.
- Understand results output and be able to see trends and patterns in the data where applicable.
Qualifications :
- Proficiency in MS Excel.
- Strong analytical communication and time management skills with an ability to exhibit critical thinking.
- Strong interpersonal skills with the ability to work in a diverse and dynamic team to adapt to change in workload and/or priorities.
- Should be ready to potentially work outside of normal office hours on a regular basis including evenings weekends and public holidays as necessary.
- Flexible with changing requirements and ability to learn new processes quickly.
Preferred/desirable:
- SQL and MS Access Visual Basic and database management systems such as SQL Server or other similar software.
- Basic knowledge of Insurance and/or reinsurance contracts and terminology.
A previous working experience using Third Party Cat modeling software (e.g. RMS AIR EQE.).
TECHNICAL SKILLS
Technical Skills Proficiency Level Required (R) /Optional (O)
Microsoft Excel 3 R
Third Party Modeling Software 3 R
Microsoft Access 3 O
Visual Basic 3 O
SQL 3 O
Programming Language
(C# VB .NET Python JavaScript) 3 O
Additional Information :
- Bachelors degree Ideally science/mathematical Degree (e.g. BS in Computer Science Engineering Mathematics Economics Information Management or Statistics.)
Remote Work :
Yes
Employment Type :
Fulltime