We are seeking a talented Actuarial Manager to join our Analytics Solutions team at Marsh Risk Consulting. This role will be based in Mumbai / Gurugram. This is a hybrid role that has a requirement of working at least three days a week in the office.

We will count on you to:

Perform actuarial, financial, and statistical analysis to assess and quantify client risks.
Examine client issues in detail, identify key drivers, and develop recommendations to support risk analysis and mitigation.
Work with internal teams and global colleagues to deliver practical, timely, and high-quality client solutions.
Support client engagements by preparing reports, presentations, and clearly communicating findings and recommendations.
Participate in and, where appropriate, lead projects, taking increasing responsibility for more complex assignments.
Contribute to client relationship management and identify opportunities for new business, where relevant.
Support the development, enhancement, and application of analytics-based tools, models, and solutions to address client needs.




Help establish and implement market-leading analytics-based approaches to assess and mitigate risk.
Conduct research to improve analytics techniques, processes, and outputs.
Identify opportunities to improve and automate processes, reducing manual effort and increasing efficiency.
Contribute to innovation and continuous improvement in analytics, reporting, and delivery methods.
Provide training, mentoring, and guidance to junior team members, as appropriate.
Share knowledge and collaborate effectively across teams to strengthen delivery capability.

What you need to have:

Degree in Statistics, Mathematics, Actuarial Science, Computer Science, Engineering, or related field.
5+ years of experience in P&C; actuarial, insurance analytics, or related technical areas.
Completed at least 10 actuarial exams under the current curriculum
Preferably passed relevant papers under the old curriculum such as CT3, CT4, CT6, and ST

📌 Manager - Actuarial Pricing(Non Life) (Mumbai)
🏢 Marsh
📍 Mumbai