Exposure Data Manager

As the Exposure Data Analytics Lead, you will:
- Lead analytics and investigations that help the business understand exposure patterns, accumulation risk, data completeness, and quality
- Define and enforce data standards, quality controls, and best practices for exposure data across business lines
- Collaborate with engineers, data platform, and analytics teams to enable downstream use (modeling, reporting, dashboards, catastrophe analytics)

Key Responsibilities

- Lead the oversight into ingestion, transformation, and normalization of exposure data from internal and external sources
- 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 and concentration risk
- Provide guidance on integrating exposure data into downstream tools (e.g. modeling engines, pricing systems, BI)

Qualifications / Skills
Required:

- 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
- Experience in insurance / reinsurance / specialty lines
- Familiarity with exposure modeling or catastrophe modeling workflows
- Experience with cloud data warehouses like Snowflake
- Experience working with ADP data tools or equivalent
- 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