Financial Data Analyst

Job Description

Job Description

We are looking for a skilled Financial Data Analyst to join our team in Woodbridge, New Jersey, on a contract basis. In this role, you will leverage your expertise in actuarial analysis, financial modeling, and data management to support key business functions and drive strategic decision-making. This opportunity is ideal for professionals with a strong background in Python, SQL, and advanced analytical techniques who thrive in dynamic environments.

Responsibilities :

• Develop and maintain actuarial models and data-driven processes using Python, R, and SQL to support insurance pricing, reserving, and risk management.
• Implement and refine month-end processes, rate change calculations, and ad-hoc analyses to ensure accuracy, completeness, and consistency of data.
• Collaborate with Actuarial and FP& A teams to automate workflows and improve the performance of financial models using Python-based scripting.
• Perform reserving analysis to estimate unpaid claim liabilities in coordination with internal and external actuaries.
• Create and update loss development triangles and incurred but not reported (IBNR) calculations based on operational and financial data.
• Assist in developing and validating actuarial assumptions for pricing, reserving, and forecasting purposes.
• Build and maintain predictive analytics models and conduct profitability analysis to support business planning.
• Conduct stress testing and scenario analysis to evaluate financial impacts and risk exposure.
• Write and optimize complex SQL queries to extract, transform, and analyze large datasets, ensuring data accuracy and integrity.
• Develop Python scripts to automate data processing, actuarial calculations, and reporting workflows.
• Proficiency in Python and SQL for data analysis, automation, and model development.
• Strong knowledge of actuarial analysis and financial modeling techniques.
• Experience in casualty insurance and familiarity with loss development triangles and IBNR calculations.
• Expertise in developing complex financial models for predictive analytics and profitability analysis.
• Ability to perform data mining and leverage advanced techniques to identify trends and opportunities.
• Hands-on experience with Python libraries such as Pandas and NumPy.
• Solid understanding of stress testing, scenario analysis, and risk assessment methodologies.
• Bachelor’s degree in actuarial science, finance, mathematics, or a related field.