Job Summary
We are seeking a highly skilled Financial Data Analyst with strong experience in Life & Annuity actuarial functions. The ideal candidate will bring deep expertise in financial data analytics, asset modeling, and programming (Python), along with a solid understanding of insurance and investment principles. This role will support actuarial modeling, financial reporting, and strategic decision-making through data-driven insights.
Key Responsibilities
• Analyze large and complex financial datasets related to life and annuity products to support actuarial valuations and reporting.
• Develop, maintain, and optimize data pipelines and analytical models using Python.
• Perform asset modeling and support Asset-Liability Management (ALM) processes.
• Collaborate with actuarial, finance, and investment teams to deliver actionable insights.
• Support financial forecasting, valuation, and risk analysis for insurance portfolios.
• Automate reporting processes and improve efficiency in data handling and analysis.
• Ensure data quality, integrity, and compliance with regulatory and internal standards.
• Assist in the development and validation of actuarial and financial models.
• Interpret and communicate analytical results to stakeholders in a clear and concise manner.
Required Qualifications & Experience
• Bachelor’s or master’s degree in actuarial science, Finance, Statistics, Mathematics, or a related field.
• 7+ years of experience in financial data analytics, preferably within life insurance or annuity domains.
• Strong hands-on expertise in Python (Pandas, NumPy, data visualization libraries).
• Proven experience in financial data analysis and reporting.
• Experience with asset modeling and/or Asset-Liability Management (ALM).
• Solid understanding of actuarial concepts in life and annuity products.
Preferred Skills
• Knowledge of insurance investment strategies and financial instruments.
• Experience working with actuarial modeling tools (e.g., Prophet, AXIS, MG-ALFA, or similar).
• Familiarity with regulatory frameworks (e.g., IFRS 17, Solvency II, US GAAP).
• Strong SQL and database management skills.
• Experience with data visualization tools (e.g., Power BI, Tableau).
• Actuarial exams progress or certification (preferred but not mandatory).
Key Competencies
• Strong analytical and problem-solving skills.
• Attention to detail and data accuracy.
• Effective communication and stakeholder management.
• Ability to work collaboratively in cross-functional teams.
• Proactive mindset with a focus on continuous improvement.
