Exposure Data Manager

Accelerant

$90K — $120K *
US-AnywhereRemote in United States
Finance & Insurance
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Experience in commercial insurance underwriting, actuarial, catastrophe modeling, or exposure management is essential.
  • Bachelor's degree in a quantitative discipline like mathematics, statistics, engineering, or actuarial science.
  • 3-4+ years of relevant experience working with exposure, insurance loss, or policy data.
  • Strong SQL skills with a focus on complex query and data transformation techniques.
  • Familiarity with exposure modeling or workflows related to catastrophe modeling.
  • Experience with cloud data warehouses, particularly Snowflake.
  • Proficient in data cleansing, validation, and QA processes.

Responsibilities

  • Lead analytics to uncover exposure patterns and risks.
  • Define data standards and quality controls for exposure data.
  • Ensure completeness and quality of exposure data through collaboration and feedback.
  • Oversee the ingestion and normalization of exposure data from various sources.
  • Validate exposure data to identify and resolve anomalies or inconsistencies.
  • Collaborate with teams to understand and support their exposure data needs.
  • Develop comprehensive documentation and process guidelines for exposure data.

Benefits

  • Opportunities for professional development and training.
  • Collaborative working environment with cross-functional teams.
  • Flexible work schedule and remote work options.
  • Access to advanced data analytics tools and technologies.
  • Health and wellness benefits to support work-life balance.
Full Job Description
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.

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 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

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