At Moody's, we unite the brightest minds to turn today's risks into tomorrow's opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody's is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we're advancing AI to move from insight to action—enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.
If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity.
Skills and CompetenciesStrong foundation in hydrology, hydraulics, climate science, applied mathematics, data science, computer science, or a related quantitative disciplineUnderstanding of machine learning fundamentals including model training and validation, overfitting, and model evaluationExperience with one or more machine learning or deep learning approaches such as Long Short-Term Memory networks, Convolutional Neural Networks, and frameworks including PyTorchPractical programming experience in Python and familiarity with scientific computing environments; experience with R, C/C++, Fortran, CUDA, or Bash is preferredAbility to analyze, validate, and interpret large geospatial, hydrological, and climate datasets using statistical methods and visualization techniquesStrong communication and collaboration skills with the ability to explain technical concepts to multidisciplinary stakeholdersExperience working with high-performance computing environments, geographic information systems, structured query language, or data assimilation techniques is desiredBasic understanding of artificial intelligence concepts, with curiosity and enthusiasm for learning how AI tools can be used to improve processes and drive efficiencyDemonstrates a growing awareness of AI risk management and a commitment to responsible and ethical AI useEducationPhD in Hydrology, Hydraulics, Coastal and Ocean Engineering, Climate Science, Applied Mathematics, Data Science, Computer Science or a related quantitative discipline Candidates with a relevant MSc and strong research or industry experience are also encouraged to applyResponsibilitiesSupport the development and validation of inland flood catastrophe models used to quantify and manage flood risk globally.
Contribute to the development and application of large-scale flood hazard model components including stochastic rainfall generation, rainfall-runoff processes, hydraulic routing, floodplain inundation, and flood defense failure mechanismsCalibrate and validate model components using observed datasets, benchmark studies, and published research to improve model performance and reliabilityAnalyze flood footprints, hazard metrics, and loss patterns using statistical methods, geospatial tools, and data visualization techniquesResearch, evaluate, and implement innovative scientific and computational approaches to advance flood hazard modeling capabilitiesExplore, prototype, and assess artificial intelligence and machine learning methods for surrogate modeling, spatial downscaling, anomaly detection, feature extraction, emulator development, and workflow automationDevelop and maintain reproducible scientific workflows, data processing pipelines, and code repositories using modern software development practicesCollaborate with scientists, engineers, and data specialists to support model development, quality assurance, and scientific innovationCommunicate research findings and modeling insights to internal stakeholders, clients, and the broader scientific community through presentations, reports, and technical discussionsAbout the TeamOur Model Development team is responsible for building industry-leading natural catastrophe models that help quantify the financial impacts of natural hazards.
The team brings together scientists, engineers, and data specialists working across flood, storm, and climate-related perils to advance risk analytics through cutting-edge research, large-scale modeling, and data innovation. By joining the Inland Flood team, you will contribute to high-impact scientific work in a collaborative environment that embraces the responsible use of artificial intelligence, machine learning, and advanced computational techniques to improve model performance and decision-making.
Moody's is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.
Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody's Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.-
Analytics & Modeling Analyst (Inland Flood) in London employer: Moody's Corporation
At Moody's, we pride ourselves on being an exceptional employer, particularly for those in the AI/ML product management space. Our collaborative work culture fosters innovation and creativity, while our commitment to employee growth ensures that you will have ample opportunities to develop your skills and advance your career. Located in a vibrant city, we offer unique advantages such as access to cutting-edge technology and a diverse client base, making your contributions impactful and rewarding.
