Actuarial Data Analytics Specialist

This position is open to individuals with a strong background in actuarial science and data analysis. The ideal candidate will have experience working with actuarial models, data visualization tools, and statistical software.

The successful applicant will be responsible for developing and maintaining actuarial models, conducting data analysis, and creating data visualizations to support business decisions.

This role involves working closely with actuaries and other stakeholders to develop and maintain actuarial models, processes, and analytical tools. The ideal candidate will have a strong understanding of actuarial concepts, insurance data, and financial modeling.

• Key Responsibilities:
• • 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.
  • Collaboration & Support:
  • • Work closely with the Actuarial and FP&A teams to support financial planning, forecasting, and profitability analysis by providing robust data models and insights.
    • Partner with Data Engineers to optimize data workflows and ensure seamless data ingestion.
    • Communicate technical results and methodologies to non-technical stakeholders in a clear and concise manner.
  • Reporting & Visualization:
  • • Develop reports, dashboards, and data visualizations using Power BI and Excel.
    • Ensure that reports comply with regulatory requirements and industry standards.
    • Presents findings and insights to key stakeholders to drive business decisions.
  • Requirements
    • Qualifications:
    • • Bachelor's degree in Mathematics, Statistics, Actuarial Science, Data Science, or a related field.
      • 3+ years of experience in actuarial analysis, data modeling, or a related technical role.
      • Understanding of Commercial P&C Insurance operations and data, Commercial Auto experience a-plus.
      • Strong programming skills in Python, and SQL. Knowledge of R a-plus.
      • Experience with NoSQL databases (e.g., MongoDB, DynamoDB) is a plus.
      • Proficiency in Power BI and Excel for data visualization and reporting.
      • Strong understanding of actuarial concepts, insurance data, and financial modeling.
    • Preferred Skills:
    • • Experience in automating data workflows and ensuring efficient data ingestion for actuarial processes.
      • Knowledge of AI, machine learning techniques and exposure to predictive modeling.
    • Soft Skills:
    • • Excellent communication and interpersonal skills.
      • Strong attention to detail, controls orientation, and commitment to delivering high-quality work.
      • Ability to handle multiple projects concurrently and meet deadlines.
      • Enthusiasm for learning new technologies and staying current in the industry.