Catastrophe Advisory Spring Co-op - College Program 2027
Marsh McLennan is hiring a Catastrophe Advisory Spring Co-op - College Program 2027 in New York, United States. Level rates it ; you can apply on Marsh McLennan.
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- On Level's scale, this role is Little AI ●○○○: aI is not part of the work.
- Level lists 620 other open roles at Marsh McLennan.
- The role was posted in the last few days.
AI in this role
Company:
Guy CarpenterDescription:
We are seeking a talented individual to join our Catastrophe Advisory team at Marsh Re. This role will be based in New York or Philadelphia. This is a hybrid role that has a requirement of working at least three days a week in the office.
Program Dates: January 2027 through June 2027 (~40 hours per week)
***This is a 6-month commitment***
As a member of our team, you will join a group of Catastrophe Advisors utilizing engineering and economic research to assess the impact of various hazard scenarios—such as earthquakes, floods, wildfires, and hurricanes—on insurance companies’ property damage and financial losses. You will collaborate with top-tier professionals in areas including catastrophe risk management, underwriting support, live event impacts, and reinsurance decision-making. You will participate in a comprehensive training program that covers a wide range of skills, including vendor models, the insurance industry, reinsurance, project management, and public speaking. Your responsibilities will include managing catastrophe modeling projects from inception to completion and contributing to innovative internal initiatives.
Why Marsh Re
At Marsh Re, you can be your best. We work on challenges that matter with colleagues who help bring out our best. Our uniquely collaborative environment will empower you to focus on your personal and professional success, learning from top specialists in the (re)insurance industry and leading you towards a rewarding and impactful career.
We will count on you to:
- Contribute to developing an inclusive work environment that respects and values differences of background, experience, and thought
- Organize client data, check data for reasonability, load data into predictive models, run the models, share insights with senior colleagues, and compile coherent and compelling narratives to help clients understand their degree of risk
- Perform basic calculations and draw conclusions from client data to assess a range of modeled outcomes for clients in support of reinsurance transaction process
- Establish and maintain strong relationships with colleagues and stakeholders
- Develop knowledge in certain region-based or peril-based areas of catastrophe risk management services through research or experience
- Take part in internal initiatives, offering ideas and feedback to improve outcomes
What you need to have:
- Progress towards a Bachelor’s degree in a quantitative or natural sciences field such as applied mathematics, statistics, engineering, operations research, finance, economics, data science, computer science, meteorology, or a demonstrated ability to learn new software and analytical concepts quickly
- An expected graduation date of December 2027 or May 2028 is preferred
- Strong academic record in major and work experience is more important than the field of study
- Curious and proactive mindset: desire and ability to lead internal initiatives and research projects to completion
- Robust data management skills: ability to manipulate, interpret, and extrapolate complex data
- Superior communication and presentation skills: an ability to translate complex technical analysis and concepts into easily understandable terms for brokers and clients
- Strong analytical, problem-solving skills and attention to detail with financial aptitude
- A collaborative, team-oriented mindset and effective interpersonal skills
- Solid computer skills including Microsoft Office (Excel, Word, PowerPoint)
- A desire and ability to grow beyond your current capabilities
- Capacity to progress multiple projects at the same time
- Legal work authorization to work in the U.S. on a permanent and ongoing basis without the need for sponsorship now or in the future
What makes you stand out:
- Experience in the insurance industry at an insurance company, reinsurance broker, reinsurer, or catastrophe model software vendor
- Experience using Microsoft SQL, Alteryx, and/or basic coding in any language
- Scientific background in meteorology and/or seismology
- An understanding of the insurance/reinsurance industry and product lines
Why join our team:
- We help you be your best through professional development opportunities, interesting work and supportive leaders
- We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have impact on colleagues, clients and communities
- Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being
The applicable hourly rate for this role is $30.00.
What's next:
Application Instructions:
- Application deadline is Sunday, October 18th at 11:59pm EST
- We are hiring in multiple locations. As you are filling out your application, you'll have the opportunity to select your desired location. Should you have interest in multiple locations, your recruiter will work with you to make those connections should that be necessary.
First Round Interviews:
- Applications are reviewed on a rolling basis.
- If selected, first-round interviews consist of an on-demand digital video interview.
- Further timing and instructions will be provided after submission of the application.
How we rate this
Catastrophe Advisory Spring Co-op - College Program 2027 at Marsh McLennan rates 32 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.
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