Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Moody's Insurance Solutions Graduate Program - Data Science

LGBT Great
City of London
1 day ago
Create job alert

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 Competencies

  • Applied experience collecting, processing, and using data to solve a problem or answer a question
  • Working knowledge of a computer programming language (examples include SQL, R/tidyverse, Python, Microsoft Excel, Julia, and Fortran) with an adaptability and willingness to learn new languages/software as required (the Model Analytics team currently primarily uses R/tidyverse and SQL)
  • Strong applied analytical, mathematical, and/or statistical foundation
  • Driven and committed, demonstrating self-motivation as well as strong team working skills
  • Critical thinking, problem-solving skills, and attention to detail
  • Ability to effectively communicate insights and analyses
  • Ability to work in dynamic environment with flexibility of tasks
  • At Moody's we believe the future of working in our industry will be shaped by AI, and as a graduate, you will be central to making that future effective and valuable for our clients

Education

  • Bachelor’s/undergraduate degree background in Climate Science, Meteorology, Hydrology, Geophysics, Earth Sciences, Geology, Natural Resources, Geographic Information Systems, Applied Mathematics, Statistics, Engineering, or similar

Preferred Qualifications

  • A Master’s or PhD degree
    Experience with or interest in: the Re/Insurance business domain/catastrophe modeling, database management/working with relational databases (SQL), Moody’s RMS products (e.g. RiskLink, Risk Modeler, Intelligent Risk Platform), data engineering, data analytics, data science, using a programming language, Collaborative code development using version control software (e.g., GitHub), Kubernetes.

About the Graduate Program/Role

As a graduate you’ll build a diverse and relevant career – learning our business, discovering your career growth opportunities, and continuing to develop your skills for years to come. Starting in September 2026, you'll join an international cohort of Moody’s Insurance Solutions graduates. You'll begin with a month-long training program, learning from our network of leading developers, scientists, product managers, customer success practitioners, and clients. Following this, you'll participate in our rotation program, gaining direct experience across various teams and disciplines. Through your rotations you will enhance your knowledge of our products, how they are built, the companies who use them, and how they get value and insight from them. Your work will span our products and markets, developing technical skills and knowledge, problem-solving skills, and communication skills.


Moody’s Insurance Solutions uses a combination of observations, reanalysis data, numerical, statistical and engineering models. We are the pioneers in the development and application of combined statistical and numerical modelling methods for the quantification of natural hazard risk, and our models are the most detailed and comprehensive models of natural catastrophes produced anywhere in the world. Our 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. The model development organization is a multidisciplinary team of catastrophe modelers including statisticians, mathematicians, physical scientists and engineers, who build models critical to our clients (Re/Insurance, regulatory, and more) and essential to the other markets we serve.


The Model Analytics team’s goal is to add efficiency and insight throughout the model development cycle and to increase the value of the models we bring to market by: eliminating surprises; telling the story of model releases; and sharing our expertise in large scale data pipelining/processing, analytics, and reporting tools. The Data Science graduate will get the opportunity to 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. In this role, 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. The ideal candidate for this position is interested in a broad range of work spanning data cleansing, data analysis/data analytics, programming, tool development, data pipelines, gaining an in-depth knowledge of catastrophe modeling and the model development cycle, and, eventually, giving detailed presentations and recommendations to leadership.


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.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.