We are seeking a talented individual to join our Actuarial team at Marsh Mc Lennan. This role will be based in Mumbai. 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:
- Help establish and implement new, market-leading analytics-based tools to assess and mitigate risk
- Develop complex models in order to assess risk and viability of risk mitigation solutions
- Examine client issues further that may not be clear and develops recommendations for analysing and mitigating risk
- Identify opportunities for new and existing business with small to mid-sized clients
- Deliver analytics-based tools to help internal and external clients quantify and mitigate risks
- Assist in the management of small to mid-sized projects to direct the team in developing analytics-based tools
- Build new one or enhance existing experience and exposure based models for risk (like D&O, Cyber, Employment practice liability, Aviation etc.)
- Develop industry based models to be used for various clients
- Improve and automate the process to minimise manual intervention
- Research and develop pricing models for Specialty Clients
- Train the junior resources on interpreting and estimating appropriate results
- Estimate technical prices and come up with layer efficiency for different insurance layers
What you need to have:
- 6+ years of experience in P&C Actuarial experience with a Pricing background
- A degree in Statistics/Mathematics/Actuarial/Computer Science/Engineering
- Completed at least 7 Actuarial exams (according to new curriculum)
- Preferable papers as per old curriculum (CT3, CT4, CT6, ST8)
- Preferable papers as per new curriculum (CS1, CS2, SP8)
- Detailed knowledge of actuarial pricing techniques
- Detail orientation, communication and interpersonal skills
- Excellent Microsoft Office skills, particularly in Excel (including VBA) and PowerPoint
- Good programming language skills on Python or R
- Excellent data visualization and report-making skills
What makes you stand out
- Strong communication skills with an ability to work in a team
- A commercial sense to apply proportionality to the depth of analytics used versus desired output
- Ability to take initiatives to strive for improvement in analytics techniques, process and output
- Statistics skills, including GLM, Bayesian probability, and other machine-learning techniques such as decision tree / random forest, etc.
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 McLennan (NYSE: MMC) is a global leader in risk, strategy and people, advising clients in 130 countries across four businesses: Marsh, Guy Carpenter, Mercer and Oliver Wyman . With annual revenue of $23 billion and more than 85,000 colleagues, Marsh McLennan helps build the confidence to thrive through the power of perspective. For more information, visit marshmclennan.com , or follow on LinkedIn and X.
Marsh McLennan 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 McLennan 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 McLennan 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.
