We are seeking a talented individual to join our Actuarial team at Marsh . This role will be based in Mumbai/Gurgaon. 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
:Reporting key metrics, self-service analytics products and analyse disparate data sets together for patterns and insights
.Exploratory data analytics, Predictive models that forecast behaviours and cost and Data story telling by using the best-in-class BI tool
sApply functional understanding of product and risk assessment and possible outcomes through scenario testin
gAnalytics orientated approach to solve real business problems

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What you need to have
The candidate should preferably have experience in insurance/reinsurance industry in their modelling/data science team up to 4 year
Cleared 4+ actuarial paper
Detailed knowledge of actuarial pricing techniques
Hands-on experience in BI tools –Qlik Sense & Tableau and Power BI (Good to have) and Analytics tools R/Python/VBA & techniques to build Model, Validate and implement.



For sure having a good data science knowledge by working on some real project
Applied math / stats skills, including GLM, Bayesian probability, and other machine-learning techniques such as decision tree / random forest etc

What makes you stand o
Strong academic rigour, and students passing with statistics and data science skills from IIT/NIT/ISC
Strong programming skills and technical individual contribution
P&C; Actuarial experience with a Pricing background (especially in areas of applying regression techniques such as GLM)
Ability to take initiatives to strive for improvement in analytics techniques, process and outp

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 current solutions and have impact for colleagues, clients and communi

📌 Lead Specialist (Mumbai)
🏢 Marsh Mclennan
📍 Mumbai