Hiring.Camp

IJP - Manager - Actuarial

Mmc

·

Today

Location
Mumbai - Hiranandani, India
Workplace
Hybrid
Type
Full-time
Department
Insurance
Seniority
Manager
Experience
5+ years
Closing date
Today
Source
Workday

Description

Company:

Marsh

Description:

We are seeking a talented Actuarial Manager to join our Actuarial 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.

Job Title : Manager - Actuarial (IMEA Region)

Location : Mumbai/Gurgaon

No. of Roles : 1

Last Date of Apply : 30th June 26

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 new curriculum

  • Preferably passed relevant papers under the old curriculum such as CT3, CT4, CT6, and ST8.

  • Preferably passed relevant papers under the new curriculum such as CS1, CS2, and SP8.

  • Strong technical knowledge of actuarial and analytical techniques

  • Proficiency in Python and/or R, including experience with data visualization and report generation.

  • Advanced Microsoft Office skills, particularly Excel (including VBA) and PowerPoint.

  • Strong analytical thinking, problem-solving, and attention to detail.

  • Good communication, interpersonal, and teamwork skills

Eligibility

  • Minimum 12 months experience as Lead Specialist (D1)/Manager(D2)

  • Should have at least “On-Track” or equivalent rating in last appraisal.

  • Should not be under any Performance Counselling Plan or had any official disciplinary action within the last 3 months.

  • Should not have applied for any other IJP in the last 3 months

Disclaimer

  • Candidates who wish to apply for inter-location positions are required to check with the Transport Help Desk (THD) to confirm if their place of residence is within the served transport service zone

  • Mention your employee id and official email address in the resume

What makes you stand out?

  • Strong knowledge of actuarial pricing, reserving, and risk transfer techniques.

  • Experience with statistical modeling, including GLM and machine learning methods such as decision trees, random forest, and XGBoost.

  • Good commercial judgment, with the ability to balance technical depth and business needs.

  • Strong communication skills and the ability to work effectively as part of a team.

  • Confidence in handling client interactions and contributing to solution-oriented discussions.

  • Ability to work well under pressure and deliver to deadlines.

  • A proactive mindset, with the ability to improve analytics techniques, processes, and outputs.

  • Ability to coach and mentor junior colleagues effectively.

Why join our team:

  • We help you be your best through professional development opportunities, interesting work and supportive leaders.

  • We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have impact for colleagues, clients and communities.

  • Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being.

Marsh (NYSE: MRSH) is a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries. With annual revenue of over $27 billion and more than 95,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective. For more information, visit marsh.com, or follow us on LinkedIn and X.

Marsh is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, caste, disability, ethnic origin, family duties, gender orientation or expression, gender reassignment, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law.

Marsh is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one “anchor day” per week on which their full team will be together in person.

Skills

PythonMachine LearningExcel

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