Actuarial Product Jobs

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Data Product Owner

MSIG North America Warren, NJ

Warren, NJ

Today

$140k - $210k/yr Full time Actuarial Analytics Azure Data Factory

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Job Description

MSIG North America offers a data driven leadership role onsite in Warren, NJ. The position commands a salary range of USD 140,000 to 210,000 per year and comes with a comprehensive benefits package. You will own the development of trusted data products that span policy structure, rate filings, exposure, pricing, loss costs, and actuarial indications to enable faster, more accurate risk and pricing decisions, bolster regulatory compliance, guide portfolio strategy, and improve product profitability. This is a collaborative, governance minded role focused on measurable business impact.

Responsibilities

Define and own the end to end data strategy across Product, Underwriting, and Actuarial domains.
Establish data standards, ownership, quality controls, lineage, and governance for internal and third party datasets including ISO, NCCI, bureau data, and vendor risk scores.
Maintain a unified data dictionary and harmonized definitions across product, underwriting, actuarial, claims, and finance teams.
Ensure data workflows meet audit, regulatory, rate filing, and compliance requirements including state Department of Insurance and NAIC obligations.
Collaborate with Legal and Compliance to support rate filing readiness, regulatory reporting, and actuarial certification requirements.
Partner with data engineering to design and improve pipelines feeding policy administration systems, rating engines, actuarial reserving models, analytics, and AI use cases.
Validate data models and transformations in Azure Data Platform, Microsoft Fabric, and Databricks.
Define and enforce data quality rules for common issues such as missing exposure fields, submission to bind data gaps, rating factor inconsistencies, endorsement mismatches, and development triangle discrepancies.
Set expectations for data availability, reliability SLAs, and lineage tracking across policy and actuarial data products.
Own the roadmap for dashboards, KPIs, and reporting across underwriting performance, product profitability, and actuarial reserve monitoring.
Enable self service analytics through Power BI and Fabric semantic models, reducing reliance on manual spreadsheet based reporting.
Standardize metrics used across Product, Underwriting, Actuarial, Claims, Finance, and Reinsurance teams, including written premium, earned premium, loss ratio, combined ratio, hit ratio, renewal retention, and rate adequacy.
Support operational decisions including risk selection, pricing adjustments, portfolio rebalancing, treaty structuring, and reserve releases.
Identify and prioritize AI and advanced analytics use cases such as predictive risk scoring, price elasticity modeling, automated extraction from submissions and policy documents, ML based reserve development, exposure analytics, and AI summaries for underwriting and memos.
Collaborate with Data Science and Azure AI Studio teams to ensure models are explainable, validated, and embedded into underwriting and actuarial workflows.
Own and prioritize the data product backlog across Product, Underwriting, and Actuarial domains.
Translate business needs into clear user stories with acceptance criteria tied to measurable value, such as improved rate adequacy or faster actuarial close.
Lead Agile ceremonies, roadmap reviews, and stakeholder demos; foster alignment across Product, Underwriting, Actuarial, Claims, Finance, Reinsurance, and IT.
Improve underwriting outcomes and risk selection through better submission data, risk scoring, and appetite visibility.
Accelerate actuarial close cycles and reduce manual data preparation in reserving and pricing workflows.
Strengthen product decisions with visibility into loss costs, exposure trends, and competitive positioning.
Enhance feedback loops from claims and finance to underwriting and product with actionable loss and portfolio insights.
Improve regulatory and rate filing readiness through governance, data documentation, and auditable actuarial data.

Requirements

5+ years of experience in data product ownership, analytics, or domain-focused data roles; P&C insurance experience strongly preferred.
Strong understanding of underwriting operations, actuarial concepts (IBNR, loss development, Schedule P, loss costs), and insurance product management.
Proven experience partnering with data engineering on pipelines, data models, and quality frameworks.
Ability to translate complex insurance and actuarial concepts into clear technical requirements.
Strong facilitation, communication, and stakeholder alignment skills.
Hands on experience with the Azure analytics ecosystem: Azure Data Platform
Hands on experience with the Azure analytics ecosystem: Microsoft Fabric
Hands on experience with the Azure analytics ecosystem: Azure Data Factory
Hands on experience with the Azure analytics ecosystem: Databricks
Hands on experience with the Azure analytics ecosystem: Azure AI Studio / Azure OpenAI
Hands on experience with the Azure analytics ecosystem: Power BI

Technologies

Azure Data Platform
Microsoft Fabric
Databricks
Azure Data Factory
Azure AI Studio / Azure OpenAI
Power BI

Benefits

Healthcare and Retirement Benefits
Comprehensive medical, dental, and vision coverage
401(k) with generous employer match and profit-sharing contribution
Wellness incentive program
Life and AD&D insurance
Flexible spending programs
Short-term and long-term disability plans
Paid time off program
Paid charitable leave
Paid parental leave
Tuition reimbursement program
Personal insurance discounts

Preferred Qualifications

Experience working directly in Underwriting, Product Management, or Actuarial teams within a P&C insurer.
Familiarity with policy administration and rating systems (Guidewire PolicyCenter, Duck Creek, Applied Epic, or similar).
Experience with submission and exposure data, SOVs, loss runs, and structured/unstructured underwriting documents.
Knowledge of actuarial methods including chain ladder, Bornhuetter-Ferguson, and Cape Cod techniques.
Familiarity with state DOI regulatory requirements, rate/form filing processes, and NAIC reporting standards.
Azure, Power BI, or data platform certifications.

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