P&C Data Analyst

Farm Family specializes in farm and ranch protection and offers a range of personal and commercial insurance products. The P&C Data Analyst develops analytical models and insights to support pricing, underwriting, and portfolio management decisions, while collaborating with actuarial, underwriting, claims, distribution, product, data, and IT teams.

Responsibilities

• Support pricing analyses, rate reviews, segmentation evaluations, portfolio monitoring, and performance assessments across Personal and Commercial Lines products
• Analyze trends in frequency, severity, retention, growth, profitability, and other key insurance performance metrics
• Partner with actuarial, underwriting, and product teams to identify business challenges and develop data-driven recommendations
• Assist in evaluating the impact of underwriting, pricing, and product changes on business performance
• Develop recurring and ad hoc analyses that support strategic and operational decision-making
• Work with large, structured and semi‑structured datasets using SQL and analytical programming languages (e.g., Python or R)
• Ensure data quality, reproducibility, and proper documentation of models, assumptions, and results
• Support adherence to model development best practices and model risk governance standards
• Support data science and predictive modeling initiatives through data preparation, feature development, exploratory analysis, and model performance reporting
• Collaborate with data scientists and actuarial partners on analytical projects involving risk segmentation, predictive modeling, and portfolio optimization
• Develop foundational skills in statistical analysis, predictive modeling, and analytical programming
• Participate in testing, monitoring, and implementation of analytical models and business rules
• Contribute to the evaluation of new data sources and analytical techniques that improve pricing and underwriting decisions
• Collaborate with actuarial, underwriting, distribution, and product stakeholders to define analytical questions and success criteria
• Translate technical analyses into clear, actionable insights using appropriate visualizations and written summaries
• Respond to feedback and iterate on analyses to better support business decisions
• Partner with technical teams to support implementation of analytical and reporting solutions
• Identify opportunities to improve reporting processes, data quality, analytical efficiency, and business insights
• Stay current on industry trends, pricing methodologies, and analytical best practices within P&C insurance
• Contribute ideas for improving models, processes, and data usage within the pricing analytics function

Preferred

• Experience in Property & Casualty insurance, preferably supporting actuarial, underwriting, claims, or product
• Familiarity with statistical analysis, predictive modeling, or machine learning concepts
• Experience with data lineage, data mapping, validation, and reconciliation processes
• Exposure to cloud-based analytics platforms and modern data environments
• Understanding of insurance data structures, coverages, rating variables, and policy lifecycle processes
• Experience working in Agile or cross-functional project environments
• Casualty Insurance
• Underwriting Support
• Claims Support
• Product Support
• Statistical Analysis
• Predictive Modeling
• Machine Learning
• Data Lineage
• Data Mapping
• Data Validation
• Data Reconciliation
• Cloud Analytics Platforms
• Modern Data Environments
• Insurance Data Structures
• Insurance Coverages
• Rating Variables
• Policy Lifecycle Processes
• Agile Project Environments
• Cross-Functional Collaboration

Benefits

• Performance-based incentives
• Health benefits
• Dental benefits
• Vision benefits
• 401(k) with company match
• Paid time off
• Professional development opportunities

Company

• U.S.-focused underwriter of specialty property and casualty insurance
• New York, New York, USA
• http://www.argogroup.com/
• Founded in 1996
• 501-1000 employees

Qualifications

• Bachelor's degree in mathematics, statistics, actuarial science, computer science, data science, or a related quantitative field
• Two to four years of relevant experience in data science, analytics, actuarial support, or related quantitative roles
• A master's degree may be considered in lieu of one to two years of experience
• Proficiency in analytical programming languages and tools (e.g., SQL, Python, R)
• Experience working with large, complex datasets
• Strong analytical thinking, problem‑solving, and communication skills
• Strong diligence and commitment to data quality
• Applicants must be legally authorized to work in the United States
• At this time, we are not able to sponsor or assume sponsorship of employment visas
• Experience in Property & Casualty insurance, preferably supporting actuarial, underwriting, claims, or product
• Familiarity with statistical analysis, predictive modeling, or machine learning concepts
• Experience with data lineage, data mapping, validation, and reconciliation processes
• Exposure to cloud-based analytics platforms and modern data environments
• Understanding of insurance data structures, coverages, rating variables, and policy lifecycle processes
• Experience working in Agile or cross-functional project environments
• A master’s degree may be considered in lieu of one to two years of experience

Required skills

• Data Lineage, Data Mapping, Data Quality Management, Data Reconciliation, Data Validation, Machine Learning, Predictive Modeling, Property and Casualty Insurance, Python, R, SQL, Statistical Analysis

Experience

• 2-4 years