Assc Analytics & Model Analyst
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Job overview
The Associate Analytics & Model Analyst supports the development, validation, and enhancement of property data and analytical solutions for property exposure assessment and catastrophe risk modeling. The role analyzes structured, semi-structured, and geospatial datasets, conducts research and quality checks, and communicates findings to stakeholders. It also contributes to process optimization and adoption of agentic AI-driven solutions while building expertise in catastrophe risk and property exposure analytics.
Skills & qualifications
Skills
Qualifications
Full job description
Skills and Competencies
- 0 to 2 years of academic, internship, or professional experience in data analytics, statistical analysis, research, or related analytical fields
- Strong proficiency in SQL for data extraction, validation, reconciliation, quality assurance, and analytical problem-solving
- Working knowledge of Python and data analysis libraries such as Pandas and NumPy to process, analyze, and interpret large datasets
- Strong analytical, logical reasoning, and critical-thinking skills, with the ability to identify trends, anomalies, and data quality issues. Effective communication and presentation skills, with the ability to translate analytical findings into actionable insights for technical and non-technical stakeholders
- Demonstrated ability to learn new tools, datasets, and analytical concepts quickly while working independently and collaboratively in a fast-paced environment
- Strong prompting and agentic AI skills, with an interest in leveraging AI-driven solutions to enhance analytical workflows and process efficiency
Education
- Bachelor’s or Master’s degree in Engineering (B.E./B.Tech, M.E./M.Tech), Data Science, Statistics, Mathematics, Computer Science, Applied Statistics, GIS, Remote Sensing, Actuarial Science, or another quantitative or analytical discipline
MBA or PGDM with a specialization in Data Analytics is also considered Responsibilities
- Analyze structured, semi-structured, and geospatial datasets to identify patterns, trends, anomalies, and opportunities for improvement.Support the development and enhancement of property insurance datasets, spatial data layers, analytical products, and data-driven solutions
- Perform exploratory research and analytical studies to support catastrophe modeling, product development, and data improvement initiatives
- Conduct data validation, reconciliation, testing, and quality assurance activities to improve data accuracy, completeness, and consistency
- Investigate data issues, document findings, identify root causes, and contribute to timely resolution efforts. Apply statistical and analytical techniques to support business insights, decision-making, and risk-related analyses
- Collaborate with analysts, modelers, data scientists, engineers, and global stakeholders across cross-functional teams. Prepare clear documentation, analytical reports, dashboards, presentations, and summaries to communicate insights and recommendations effectively
- Contribute to process optimization, automation initiatives, and the adoption of agentic AI-driven solutions to improve operational efficiency
- Develop expertise in catastrophe risk, property exposure analytics, geospatial data, and related analytical tools and methodologies
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. Working with large-scale property, geospatial, and risk-related datasets, the team focuses on improving the accuracy, consistency, completeness, and usability of analytical information. This role offers an excellent opportunity to collaborate with multidisciplinary teams across India, London, and the United States while building expertise in data analytics, statistical analysis, property intelligence, data quality, and risk-focused products in a highly collaborative and innovation-driven environment.
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