Data Scientist for Catastrophe Modeling
1 day ago
About the Company
">At Moody's Investors Service, we are a leader in credit risk assessment and financial research. We empower clients to make informed decisions by providing deep insights into the creditworthiness of companies and governments.
">The Opportunity
">We are seeking a talented Data Scientist to join our Moody's Insurance Solutions team. As a graduate, you will work closely with our top developers, scientists, product managers, customer success experts, and clients to help provide insight into upcoming models, eliminate surprises, and ensure readiness for model releases.
">Your Responsibilities
">- You will work with a broad range of internal and client data, and with data pipelining, processing, and visualization tools that are being increasingly utilized across teams and organizations within Moody's Insurance Solutions.
- You will have the opportunity to gain an in-depth knowledge of catastrophe modeling and the model development cycle, and eventually give detailed presentations and recommendations to leadership.
- You will work closely with the Model Development, Model Analytics, Model Documentation, Model Specialist, Consulting, and other teams to help provide insight into upcoming models, eliminate surprises, and ensure readiness for model releases.
About the Team
">Our local team has over fifty Ph.D. scientists and engineers based in London, building mathematical models that predict the distributions of possible damage due to the effects of tropical storms, extra-tropical storms, thunderstorms, storm-surges, and freshwater floods.
">What We Offer
">We offer a competitive salary of $80,000 per year, plus benefits including health insurance, retirement savings plan, and paid time off. Additionally, you will have the opportunity to work on exciting projects, collaborate with a diverse group of professionals, and gain valuable experience in data science and catastrophe modeling.
">Requirements
">- A Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field.
- Strong programming skills in R, Python, or SQL.
- Experience with data analysis and visualization tools such as Tableau, Power BI, or D3.js.
- Excellent communication and collaboration skills.
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