Exposure Data Manager
Required skills
- commercial insurance underwriting
- actuarial
- catastrophe modeling
- exposure management
- exposure data
- insurance loss data
- policy data
- SQL
- complex query
- data transformation
Nice to have
- MGA
- delegated authority exposure data
- Python
- Git
- dbt
- Airflow
Role summary
Accelerant is a data-driven risk exchange transforming specialty insurance. The Exposure Data Manager will lead analytics and investigations into exposure patterns and accumulation risk, defining and enforcing data standards and quality controls for exposure data. This role requires deep insurance domain expertise, with no prior insurance experience candidates being considered. Key responsibilities include overseeing data ingestion, transformation, and normalization, validating data quality, partnering with actuarial and underwriting teams, developing documentation, supporting analytical use cases, and building data quality KPIs.
About Us
Accelerant(NYSE: ARX)isais a data-driven risk exchangetransforming specialty insurance through data,advanced analytics,andAI driven insights.Our marketplace and proprietary technology platformempowerssmall-to-medium businesses to thrive 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 Accelerant Risk Exchangein the last 12 months ended Q3 2025.For more information, please visit .
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 underwriting and exposure decisions. Candidates with no prior insurance experience will not be considered.
As the Exposure Data Manager, you will:
- Lead analytics and investigations that help the business understand exposure patterns and accumulation risk
- Define and enforce data standards, quality controls, and best practices for exposure data across business lines
- Own data quality and completeness - you not only collect feedback, but intuit 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
- Lead the business oversight into ingestion, transformation, and normalization of exposure data from internal and external sources, using underwriting, Actuarial or adjacent knowledge - Validate and QA exposure data: identify anomalies, gaps, duplicates, inconsistencies, and drive improvements- Partner with actuarial, underwriting, catastrophe modeling, and product teams to understand their exposure needs- Develop and maintain exposure data documentation, data dictionaries, and process guidelines- Enable and support analytical use cases (e.g. accumulation risk, portfolio stress testing, scenario analysis)- Build, monitor and track data quality KPIs, build dashboards or alerts to surface issues proactively- Support ad hoc analysis to diagnose exposure trends, concentration risk, rate analysis, and required underwriting actions - Provide guidance on integrating exposure data into downstream tools (e.g. modeling engines, pricing systems, BI)Qualifications / Skills
Required:
- Must have experience in commercial insurance underwriting, 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 related domain- Strong proficiency in SQL; complex query and data transformation skills- Familiarity with exposure modeling or catastrophe modeling workflows- Experience with cloud data warehouses like Snowflake- Experience working with insurance carrier data pipelines- Experience in data cleansing, validation, and QA- Analytical mindset 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
