Overview
Skills
Job Details
Job Title:- Quantitative Financial Data Analyst (Actuary)
Location:- Remote (EST)
Duration:- Contract
Job Description
- A functional analyst or actuary with Python scripting experience to run and automate insurance-related reports (loss ratios, premiums, collections, claims, etc.).
- Strong understanding of the insurance business (e.g., niche segments like tree service general liability) with skills in SQL and Python for building financial models.
- Ability to support reserving, pricing, and forecasting functions through data-driven processes and reporting, working closely with actuarial and FP&A teams.
Model Development & Maintenance
Develop and maintain actuarial models and data-driven processes using Python, R, and SQL to support insurance pricing, reserving, and risk management.
Implement and enhance month-end processes, rate change calculations, and ad-hoc analyses with a focus on completeness, accuracy, and consistency to ensure data is of the highest quality.
Work with the Actuarial and Financial Planning and Analysis (FP&A) teams to automate and improve model performance using Python-based scripting and automation.
Ensure accuracy, consistency, and efficiency of actuarial models and methodologies.
Traditional Actuarial Tasks
Support reserving analysis to estimate unpaid claim liabilities primarily in partnership with internal and external actuaries.
Develop and maintain loss development triangles and incurred but not reported (IBNR) calculations both based on financial and operational data (e.g., claims closing ratios).
Support the development and validation of actuarial assumptions for pricing, reserving, and forecasting.
Develop and regularly report on rate change calculations including bifurcation of exposure changes from pure rate by line of business.
Financial Modeling & Risk Assessment
Conduct stress testing and scenario analysis to assess financial impacts.
Develop, update, and maintain models for predictive analytics, profitability analysis, and business planning.
Assist in forecasting financial performance and evaluating risk exposure.
Data Management & Analysis
Write complex queries in SQL to extract and transform data, leveraging Python for advanced data processing and automation.
Build queries with a controls-oriented focus to ensure accuracy, completeness, Analyze large datasets using Python libraries such as Pandas and NumPy to identify trends, patterns, and opportunities for optimization.
Develop and implement Python scripts to automate data processing, actuarial calculations, and reporting workflows.