Financial Data Analyst

• 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