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Actuarial - Group Manager - Gurgaon

wnsglobalservices144

Gurgaon, HR, India permanent

Posted: April 13, 2026

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Quick Summary

The Actuarial - Group Manager role is responsible for leading and managing a team of actuaries to design and implement intelligent business solutions for clients across various industries.

Job Description

WNS, part of Capgemini, is an Agentic AI-powered leader in intelligent operations and transformation, serving more than 700 clients across 10 industries, including Banking and Financial Services, Healthcare, Insurance, Shipping and Logistics, and Travel and Hospitality. We bring together deep domain excellence – WNS’ core differentiator – with AI-powered platforms and analytics to help businesses innovate, scale, adapt and build resilience in a world defined by disruption.Our purpose is clear: to enable lasting business value by designing intelligent, human-led solutions that deliver sustainable outcomes and a differentiated impact. With three global headquarters across four continents, operations in 13 countries, 65 delivery centers and more than 66,000 employees, WNS combines scale, expertise and execution to create meaningful, measurable impact.

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.

• 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).

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