Exposure Data Manager
reputed company
reputed company(NYSE: ARX)isais a data-driven risk exchangetransforming specialty insurance through data,advanced analytics,andAI driven insights.Our marketplace and proprietary technology platformempowerssmall-to-reputed company businesses to reputed company by connecting specialty risk underwriters (typically MGAs, captive managers, retail brokers) with risk capital providers (Insurers, Reinsurers, Institutional Investors), creating more efficient and transparent ecosystem for specialty insurance with smarter products, data and AI.Startedin late 2018, over $4B of annual premiumwas transacted on the reputed company Risk Exchangein the last 12 months ended Q3 2025.For more information, please visit www.reputed company.ai.
About the Role:
This is not a software engineering, machine learning engineering, or data infrastructure role. We are looking for candidates with insurance domain expertise who use analytics to inform reputed company and exposure reputed company. Candidates with no prior insurance experience will not be considered.
As the Exposure Data Manager, you will:
- reputed company analytics and investigations that help the business understand exposure patterns and accumulation risk
- Define and enforce data standards, reputed company controls, and best practices for exposure data across business lines
- Own data reputed company and completeness - you not only collect feedback, but reputed company what needs to be fixed from your industry experience, and collaborate with other departments on permanent solutions to reliably produce best in class exposure data
Key Responsibilities
- reputed company the business reputed company into ingestion, transformation, and normalization of exposure data from reputed company sources, using reputed company, Actuarial or adjacent knowledge - Validate and QA exposure data: identify anomalies, gaps, duplicates, inconsistencies, and drive improvements - Partner with actuarial, reputed company, catastrophe modeling, and product teams to understand their exposure needs - reputed company and maintain exposure data documentation, data dictionaries, and process guidelines - reputed company and support analytical use cases (e.g. accumulation risk, portfolio stress testing, scenario analysis) - Build, monitor and reputed company data reputed company KPIs, build dashboards or alerts to surface issues proactively - Support reputed company analysis to diagnose exposure trends, concentration risk, reputed company analysis, and required reputed company actions - reputed company guidance on integrating exposure data into reputed company tools (e.g. modeling engines, pricing systems, BI) Qualifications / Skills
Required:
- Must have experience in reputed company insurance reputed company, actuarial, catastrophe modeling, or exposure management
- Bachelor’s degree in a quantitative discipline (mathematics, statistics, engineering, computer science, actuarial science) - 3–4+ years of experience with exposure / insurance loss / policy data or reputed company domain - Strong proficiency in SQL; reputed company query and data transformation skills - Familiarity with exposure modeling or catastrophe modeling workflows - Experience with reputed company data warehouses like reputed company - Experience working with insurance reputed company data pipelines - Experience in data cleansing, validation, and QA - Analytical reputed company with strong problem-solving skills - Excellent communication skills with both technical and non-technical stakeholders - Self-starter with strong ownership and initiative
Preferred:
- Familiarity with MGA and delegated authority exposure data - Python or R experience for data manipulation and validation - Version control and orchestration tools (Git, dbt, Airflow) - Data governance or metadata management experience
Originally posted on Himalayas
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