Lead - Insurance Underwriting & Loss Ontology

Onsite 4 days per week

Note: This is a full-time role and we do not offer C2C or C2H employment and are not able to sponsor visas for this position.

The Lead - Insurance Underwriting & Loss Ontology is responsible for defining, governing, and advancing the enterprise ontology supporting insurance coverage, exposure, underwriting, claims, and loss information across Acrisure's retail brokerage, wholesale, and specialty insurance businesses. Embedded within the Acrisure Data Ontology Department, this domain expert ensures consistent business meaning, semantic alignment, and data integrity across operational systems, data integrations, master data, analytics, and AI-driven applications. Working closely with business leaders, application owners, product teams, and data consumers, the role enables a unified and scalable foundation for insurance data management and decision-making across the enterprise.

Core Functions:

1. Develop & Manage Domain Ontology: Develop and manage the Coverage, Exposure, Underwriting, Claims, and Loss domain ontology, including enterprise data models, schemas, data dictionaries, naming standards, business definitions, classifications, hierarchies, and business logic. Ensure domain structures accurately represent insurance risk, coverage, exposure, underwriting, and loss concepts while supporting consistent use across Acrisure's retail, wholesale, and specialty business units.

2. Integrate Internal, Carrier & Third-Party Data: Design data integration of first-party, secondparty, and third-party data into the Coverage, Exposure, Underwriting, Claims, and Loss ontology. Establish standards and mappings for internal business data, carrier and market data, IVANS transactions, loss runs, valuation data, catastrophe and geospatial data, industry benchmarks, and other external data sources. Ensure all data is accurately aligned to ontology standards, business definitions, and domain schemas to create a unified, trusted view of insurance risk, exposure, underwriting performance, and loss experience across the enterprise.

3. Govern Critical Insurance Data: Establish and maintain governance standards for underwriting, exposure, coverage, claims, and loss data by identifying authoritative sources, defining business rules, managing data quality requirements, and resolving inconsistencies in definitions, classifications, and data usage. Ensure critical insurance data remains trusted, standardized, and fit for enterprise reporting, analytics, and operational use.

4. Align Domain Data: Lead the identification, onboarding, and alignment of underwriting, policy, claims, carrier, exposure, and loss data from source systems across Acrisure's retail, wholesale, and specialty business units. Partner with business and technology stakeholders to discover new data sources, define ontology mappings, and ensure data is extracted, transformed, and conformed to enterprise ontology standards. Establish and maintain lineage, business rules, and data requirements that enable trusted, consistent domain data to be consumed across reporting, analytics, AI, and operational workflows.

5. Enable Analytics & AI: Partner with analytics, reporting, data science, and technology teams to translate underwriting and loss business concepts into trusted data assets, metrics, and derived calculations. Ensure consistent definitions and business logic for key performance indicators, profitability analysis, portfolio management, loss reporting, predictive models, AI solutions, and enterprise decision-making.

6. Monitor Industry Standards & Data Requirements: Maintain deep expertise in insurance industry data standards, regulatory requirements, carrier reporting specifications, and market data exchange frameworks. Stay current on evolving standards such as ACORD, IVANS, carrier data requirements, and regulatory reporting obligations to ensure the ontology supports the accurate creation and exchange of policy documents, applications, submissions, binders, certificates of insurance, evidence of coverage, proofs of insurance, loss reporting, and other operational and regulatory insurance transactions. Partner with business and technology teams to proactively incorporate industry changes into ontology models, data definitions, and business rules.

Core Relationships: For the Lead - Insurance Underwriting & Loss Ontology, the core relationships and stakeholders reflect the groups that create, manage, consume, analyze, and govern underwriting and loss-related data across the enterprise.

1. Underwriting Leaders & Teams: Partner with underwriting leaders and subject matter experts to define exposure, coverage, risk assessment, pricing, and profitability concepts within the ontology. Ensure underwriting requirements, risk evaluation methodologies, carrier submission processes, and portfolio management metrics are accurately represented in enterprise data models and business definitions.

2. Claims Leaders & Teams: Collaborate with claims leadership and operations teams to establish consistent definitions for claims, reserves, payments, recoveries, cause of loss, severity, and loss development metrics. Ensure claims and loss data are accurately represented within the ontology to support claims operations, loss analysis, and performance reporting.

3. Agency, Wholesale & Specialty Business Leaders: Work closely with retail, wholesale, MGA, and specialty business leaders to understand unique underwriting, coverage, exposure, and claims processes across business units. Ensure the ontology accommodates business-specific requirements while maintaining enterprise consistency and standardization.

4. Carrier Partners & Market Relationships: Partner with carrier stakeholders to understand carrier-specific coverage structures, underwriting requirements, loss reporting standards, appetite data, submission requirements, and policy administration practices. Ensure carrier data can be standardized and integrated into the enterprise ontology while preserving critical business context.

5. Data & Analytics Teams: Collaborate with analytics, business intelligence, data science, and actuarial teams to define trusted metrics, dimensions, derived attributes, and business logic. Ensure underwriting, exposure, coverage, and loss data can be consistently leveraged for reporting, forecasting, profitability analysis, AI, and advanced analytics initiatives.

6. Technology & Enterprise Architecture Teams: Partner with enterprise architecture, application owners, integration teams, and engineering organizations to align source system data with ontology standards. Provide business definitions, mappings, lineage requirements, and domain expertise that support enterprise data products, workflows, and technology solutions.

7. Data Governance & Master Data Management: Work with data governance, MDM, data quality, and stewardship teams to establish authoritative sources, data ownership, governance policies, and quality standards for coverage, exposure, underwriting, claims, and loss information across the enterprise.

8. External Data & Industry Partners: Collaborate with providers of carrier, IVANS, catastrophe, geospatial, valuation, benchmarking, and other third-party insurance data to ensure external data sources are properly understood, standardized, and incorporated into the ontology in support of underwriting, risk management, and loss analysis.

9. Legal, Compliance & Regulatory Teams: Partner with legal, compliance, and regulatory stakeholders to ensure ontology structures and business definitions support insurance regulatory requirements, carrier reporting obligations, audits, certificates, evidence of coverage, and other compliance-related processes.

10. Product, Workflow & AI Solution Owners: Work with product managers, workflow owners, and AI solution teams to ensure coverage, exposure, underwriting, and loss concepts are accurately represented and consumable across enterprise applications, operational workflows, digital experiences, reporting platforms, and AI-powered business solutions.

Core Applications Supported: Provide domain expertise, data alignment, and ongoing support for key applications including the external portals and other core submission and underwriting applications to ensure consistent data usage and adherence to ontology and industry standards. Qualifications Deep expertise in how insurance risk is evaluated, bound, serviced, and ultimately produces loss outcomes. Ideal candidates have operational business knowledge, data governance, analytics enablement, and cross-system data integration experience.

1. Insurance Coverage Expertise

• Deep knowledge of commercial and personal lines insurance coverages across retail, wholesale, and specialty business units.

• Understanding of policy structures, coverages, endorsements, exclusions, limits, deductibles, sublimits, and conditions.

• Ability to interpret carrier forms, manuscript forms, and policy language.

• Knowledge of how coverages vary by carrier, product, state, and program.

2. Exposure Data Expertise

• Expertise in the exposure information used to evaluate and price risk.

• Understanding of insured locations, operations, property values, payroll, sales, vehicle schedules, employee counts, occupancy, classifications, and industry-specific exposures.

• Knowledge of underwriting submission data captured through ACORD forms and carrier applications.

• Ability to standardize and govern exposure data across diverse business units and source systems.

3. Underwriting Expertise

• Understanding of underwriting workflows from submission through quote, bind, issuance, renewal, and endorsement.

• Knowledge of underwriting appetite, risk selection, eligibility rules, and pricing factors.

• Experience with loss ratio analysis, risk segmentation, predictive modeling inputs, and portfolio management.

• Ability to translate underwriting concepts into enterprise data structures, business rules, and ontology definitions.

4. Claims & Loss Expertise

• Deep understanding of the claims lifecycle including FNOL (First Notice of Loss), investigation, reserving, settlement, and closure.

• Knowledge of indemnity payments, expense payments, reserves, recoveries, subrogation, salvage, and litigation.

• Experience analyzing claim frequency, severity, incurred losses, paid losses, and loss development.

• Understanding of how loss outcomes connect back to underwriting decisions and exposure characteristics.

Candidates should be comfortable with an on-site presence to support collaboration, team leadership, and cross-functional partnership.

Employee Benefits

We also offer our employees a comprehensive suite of benefits and perks, including:

• Physical Wellness:Comprehensive medical insurance, dental insurance, and vision insurance; life and disability insurance; fertility benefits; wellness resources; and paid sick time.

• Mental Wellness:Generous paid time off and holidays; Employee Assistance Program (EAP); and a complimentary Calm app subscription.

• Financial Wellness:Immediate vesting in a 401(k) plan; Health Savings Account (HSA) and Flexible Spending Account (FSA) options; commuter benefits; and employee discount programs.

• Family Care:Paid maternity leave and paid paternity leave (including for adoptive parents); legal plan options; and pet insurance coverage.

• … and so much more!

This list is not exhaustive of all available benefits. Eligibility and waiting periods may apply to certain offerings. Benefits may vary based on subsidiary entity and geographic location.