Role: Python developer (Guidewire PolicyCenter)
Location: San Antonio, TX - onsite
Duration: 6+ months
$65/hr C2C
Python with rating knowledge
"Data Manipulation: You must be highly proficient in Pandas and NumPy to clean, sort, and process large historical datasets.Machine Learning: Familiarity with Scikit-Learn is essential for building classification and regression algorithms that predict risk.Statistical Modeling: Use packages like Statsmodels to apply Generalized Linear Models (GLMs), which are the industry standard for insurance ratemaking.Version Control: Standard team workflows require the use of Git to manage code updates and track model versions securely.
remium Calculation: Using age, health status, and vehicle data to price policies and set premiums.Underwriting: Assessing the statistical risk of insuring an individual or business."
Key Roles & ResponsibilitiesRating Engine Development: Write and maintain backend code that ingests risk attributes and calculates accurate policy premiums, discounts, and surcharges.Actuarial Translation: Collaborate with actuaries to translate manual rate manuals (like those filed in SERFF) and statistical models into executable, production-grade code.Data Pipelines & ETL: Build and manage data pipelines using libraries like Pandas and NumPy to process historical claims and policy data.Predictive Pricing Modeling: Develop machine learning algorithms (e.g., using Scikit-Learn) to evaluate risk loss and optimize pricing models.Compliance & Auditing: Ensure rating logic complies with state insurance regulations by building logging and auditing mechanisms directly into the code.Core Technical SkillsProgramming Languages: Advanced proficiency in Python and SQL.Python Libraries: Pandas and NumPy for data manipulation; Scikit-Learn for predictive modeling.Insurance Platforms: Familiarity with modern underwriting and actuarial platforms like Guidewire, hx Renew (hyperexponential), or Openkoda.Cloud & DevOps: AWS (Lambda, S3) or Azure services, Docker, and CI/CD tools.Version Control: Git / GitHub for collaborative software development.Domain-Specific KnowledgeRatemaking Fundamentals: Understanding of loss cost modeling, frequency vs. severity distributions, and base rate calculations.Underwriting Rules: Knowledge of how Motor Vehicle Records (MVR), garaging territories, and vehicle safety features impact risk tiering.Telematics: Experience parsing and utilizing data from usage-based insurance (UBI) trackers to adjust rates based on driving behavior.
SQL (Structured Query Language): The coding language used to pull raw data from massive insurance databases.Predictive Modeling (Machine Learning): Using code to guess which drivers will cost the company the most money.Data Visualization: Using Python packages like Matplotlib or Seaborn to turn complex pricing data into easy-to-read charts for business leaders.Cloud Computing (AWS/Azure): Running massive pricing models on remote computers so your laptop does not crash.Regulatory Compliance: Understanding state laws and rules to ensure your Python pricing models do not violate fair housing or discrimination rules.
Role Descriptions: Key Roles & ResponsibilitiesRating Engine Development: Write and maintain backend code that ingests risk attributes and calculates accurate policy premiums| discounts| and surcharges.Actuarial Translation: Collaborate with actuaries to translate manual rate manuals (like those filed in SERFF) and statistical models into executable| production-grade code.Data Pipelines & ETL: Build and manage data pipelines using libraries like Pandas and NumPy to process historical claims and policy data.Predictive Pricing Modeling: Develop machine learning algorithms (e.g.| using Scikit-Learn) to evaluate risk loss and optimize pricing models.Compliance & Auditing: Ensure rating logic complies with state insurance regulations by building logging and auditing mechanisms directly into the code.Core Technical SkillsProgramming Languages: Advanced proficiency in Python and SQL.Python Libraries: Pandas and NumPy for data manipulation; Scikit-Learn for predictive modeling.Insurance Platforms: Familiarity with modern underwriting and actuarial platforms like Guidewire| hx Renew (hyperexponential)| or Openkoda.Cloud & DevOps: AWS (Lambda| S3) or Azure services| Docker| and CI/CD tools.Version Control: Git / GitHub for collaborative software development.Domain-Specific KnowledgeRatemaking Fundamentals: Understanding of loss cost modeling| frequency vs. severity distributions| and base rate calculations.Underwriting Rules: Knowledge of how Motor Vehicle Records (MVR)| garaging territories| and vehicle safety features impact risk tiering.Telematics: Experience parsing and utilizing data from usage-based insurance (UBI) trackers to adjust rates based on driving behavior.
Essential Skills: "Data Manipulation: You must be highly proficient in Pandas and NumPy to clean| sort| and process large historical datasets.Machine Learning: Familiarity with Scikit-Learn is essential for building classification and regression algorithms that predict risk.Statistical Modeling: Use packages like Statsmodels to apply Generalized Linear Models (GLMs)| which are the industry standard for insurance ratemaking.Version Control: Standard team workflows require the use of Git to manage code updates and track model versions securely.remium Calculation: Using age| health status| and vehicle data to price policies and set premiums.Underwriting: Assessing the statistical risk of insuring an individual or business."SQL (Structured Query Language): The coding language used to pull raw data from massive insurance databases.Predictive Modeling (Machine Learning): Using code to guess which drivers will cost the company the most money.Data Visualization: Using Python packages like Matplotlib or Seaborn to turn complex pricing data into easy-to-read charts for business leaders.Cloud Computing (AWS/Azure): Running massive pricing models on remote computers so your laptop does not crash.Regulatory Compliance: Understanding state laws and rules to ensure your Python pricing models do not violate fair housing or discrimination rules.
Diverse Lynx LLC is an Equal Employment Opportunity employer. All qualified applicants will receive due consideration for employment without any discrimination. All applicants will be evaluated solely on the basis of their ability, competence and their proven capability to perform the functions outlined in the corresponding role. We promote and support a diverse workforce across all levels in the company.