Analytics & Modeling Analyst

Job Summary

At Moodys, 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.

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.

Experience level: Experienced Hire

Job category: Engineering & Technology

Line of business: Insurance

Skills and Competencies

• 3 to 5 years of experience in data analytics, statistical analysis, analytical research, spatial data analysis, or related quantitative disciplines, with strong proficiency in SQL and Python
• Hands-on experience using Python libraries such as Pandas and NumPy to analyze, validate, transform, and interpret large datasets
  Strong analytical, critical thinking, and problem-solving skills, with the ability to translate business requirements into actionable insights and communicate findings to diverse stakeholders
• Experience with data quality assessment, testing, reconciliation, automation, and process improvement initiatives; familiarity with AI-assisted workflows and effective prompting techniques
• Exposure to visualization tools such as Tableau or Power BI, cloud-based analytical environments, data pipelines, or ETL workflows is preferred
• Knowledge of GIS, catastrophe modeling, insurance analytics, risk management, machine learning, or related analytical domains is advantageous

Education

• Bachelors or Masters degree in Engineering, Data Science, Statistics, Mathematics, Computer Science, GIS, Remote Sensing, Actuarial Science, Business Analytics, or another quantitative discipline with relevant professional experience. OR
• PhD in a quantitative or analytical field with up to 2 years of relevant experience

Responsibilities

• Analyze structured, semi-structured, and geospatial datasets to uncover trends, identify anomalies, and generate insights that support business and modeling decisions
• Support the development and enhancement of property insurance datasets, analytical products, spatial data layers, and reporting solutions
• Apply statistical and analytical techniques to improve data quality, validate datasets, investigate issues, and contribute to model and product improvement initiatives
• Partner with analysts, data scientists, modelers, engineers, and global stakeholders to deliver scalable, data-driven solutions
• Develop clear documentation, analytical summaries, dashboards, presentations, and reports that enable informed decision-making
• Contribute to automation, operational efficiency, and innovation initiatives, including the adoption of AI-driven and agentic solutions
• Build expertise in catastrophe risk, property exposure analytics, and related data and modeling technologies while expanding your analytical capabilities

About the Team

The Data Analytics & Solutions team within Model Development is responsible for developing, validating, and enhancing property data and analytical solutions that support property exposure assessment and catastrophe risk modeling. The team works with large-scale property, geospatial, and risk-related datasets to improve data accuracy, consistency, and usability. This role offers the opportunity to collaborate with multidisciplinary teams across India, London, and the United States while building deep expertise in analytics, data quality, property intelligence, and risk-focused products.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.