Earnix / Rating Developer

Job Description

We are seeking an experienced Earnix / Rating Developer to develop, maintain, and optimize pricing and predictive models for insurance products. The ideal candidate will have strong expertise in Earnix, pricing analytics, predictive modeling, SQL, Python/R, and data visualization, along with experience supporting pricing strategies and implementing analytical solutions for business stakeholders.

Key Responsibilities

Pricing & Predictive Modeling

• Develop, maintain, and optimize pricing and predictive models using statistical and machine learning techniques.
• Analyze large datasets to identify pricing trends, customer behavior, and profitability drivers.
• Support pricing strategy decisions through scenario analysis, forecasting, and simulations.
• Validate model performance to ensure accuracy, consistency, and compliance with governance standards.

Analytics & Reporting

• Build dashboards, reports, and visualizations using Tableau and Power BI.
• Conduct A/B testing and impact analysis for pricing changes and product enhancements.
• Automate recurring analytical and reporting processes where possible.
• Monitor market trends, competitor pricing, and customer behavior to recommend pricing adjustments.

Business Collaboration

• Collaborate with business, underwriting, product, and engineering teams to implement pricing solutions.
• Translate business requirements into analytical solutions and technical specifications.
• Support regulatory and audit requests related to pricing models and data usage.

Required Technical Skills

Pricing & Analytics

• Earnix Rating
• Pricing Analytics
• Predictive Modeling
• Statistical Analysis
• Machine Learning Concepts
• Data Science

Programming & Databases

• SQL
• Python or R
• Excel

Data Visualization

• Tableau
• Power BI

Modeling Techniques

• Regression Models
• Classification Models
• Forecasting Techniques
• Data Mining
• Data Segmentation

Required Experience

• 6–10+ years of overall IT/Analytics experience.
• 3+ years of hands-on experience in:
  • Pricing Analytics
  • Predictive Modeling
  • Data Science
  • Insurance / Financial Services Analytics (preferred)
• Strong expertise in statistical analysis, predictive modeling, and machine learning concepts.
• Experience building pricing models and supporting business pricing strategies.
• Proficiency with SQL, Python or R, Excel, Tableau, and Power BI.
• Experience with regression models, classification models, forecasting techniques, data mining, and segmentation.
• Bachelor''s degree in Data Science, Statistics, Mathematics, Economics, Computer Science, Actuarial Science, Engineering, or a related quantitative field.