Marsh McLennanCatastrophe Modeler - Marsh Re - Tokyo, Japan
Marsh McLennan is hiring a Catastrophe Modeler - Marsh Re - Tokyo, Japan (Japan). Level rates it ; you can apply on Marsh McLennan.
Level's read on this job
- Little AI ●○○○ is how Level rates this role: aI is not part of the work.
- The posting mentions Spreadsheets, catastrophe modeling and risk analysis among its tools and skills.
- Level classes it as a mid-level role.
- Marsh McLennan has 622 other open roles on Level.
- Posted within the past two weeks.
AI in this role
Support catastrophe risk analyses, validate client exposure data, and research natural and man-made perils as a Catastrophe Modeler.
Company:
MarshDescription:
Catastrophe ModelerTokyo, Japan
As a Catastrophe Modeler, you will support catastrophe risk analyses by preparing client exposure data, assisting with model-based analysis, and helping translate potential risk and loss results into clear client deliverables. You will also research relevant natural and man-made catastrophe perils to strengthen our analysis and reporting.
We will count on you to:
- Gather, organize, review, and validate raw client exposure data for use in catastrophe risk analyses.
- Assist with basic analyses using existing catastrophe risk models, with guidance from senior project team members.
- Prepare and format data sets for analysis and review by senior project team members.
- Support the preparation of client summaries, presentations, and reports covering potential risk and loss results.
- Research industry publications and scientific papers on specific or regional natural and man-made perils, summarizing relevant findings for use in analyses and client reports.
What you need to have:
- Strong attention to detail and the ability to organize, review, and manage data accurately.
- Ability to perform basic data analysis and follow established analytical processes.
- Strong written and verbal communication skills, with the ability to summarize technical information clearly.
- Ability to conduct research, evaluate relevant information, and produce concise summaries.
- A collaborative mindset and willingness to learn from senior project team members while managing assigned tasks responsibly.
What makes you stand out:
- Exposure to catastrophe modelling, risk analysis, insurance, reinsurance, or related financial services.
- Experience working with exposure data, analytical tools, spreadsheets, or data visualization and reporting applications.
- Familiarity with natural catastrophe perils, man-made catastrophes, or regional risk research.
- Experience preparing client-facing presentations, reports, or analytical summaries.
- Knowledge of the Japanese insurance or reinsurance market, or the ability to work effectively in both Japanese and English.
How we rate this
Catastrophe Modeler - Marsh Re - Tokyo, Japan at Marsh McLennan rates 0 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where catastrophe modeling was part of your work. What did you do?
- Tell me about a project where risk analysis was part of your work. What did you do?
- Tell me about a project where data validation was part of your work. What did you do?
- Tell me about a project where research was part of your work. What did you do?
- Walk me through how you've used Spreadsheets in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Catastrophe Modeling, Risk Analysis, Data Validation, Research, and Spreadsheets. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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