Senior Manager - Pricing Actuarial Risk Consulting

We are looking for a talented and dynamic individual to join our Risk Consulting team at Knowledge Services. This role is based in Mumbai. This is a hybrid role that has a requirement of working at least three days a week in the office.

The Emerging Risks Group (ERG) is one of the fastest growing verticals under the Strategic Risk Consulting arm of Marsh Advisory and work in areas of Cyber, Climate, Supply Chain, Geopolitics, and other portfolio of risks. The actuarial colleagues within supports to build and run models to deliver client projects. The ERG is seeking candidates for the following position based in either Hiranandani, Mumbai or DLF Cyber City, Gurugram office:

Manager/Senior Manager, Actuarial Risk Consulting

We will count on you to:

• Assess the need, effectiveness and discovery of new data sources and data gathering techniques through extensive research
• Conduct comprehensive actuarial analysis and Modeling to assess Cyber risk exposures, utilizing Monte Carlo simulations to project potential scenarios and evaluate risk outcomes
• Develop new and enhance existing actuarial models, incorporating statistical techniques and algorithms to analyse and predict risk exposures and potential losses
• Leverage Python to build models beginner to moderate level experience in Python will stand in good stead.
• Utilize Excel extensively for data analysis, modelling, and reporting purposes, ensuring accuracy and efficiency in calculations and data manipulation
• Analyse frequency and severity distributions to estimate probabilities and impact of potential cyber incidents, utilizing appropriate statistical methods and actuarial techniques
• Calculate VaR and TVaR, providing insights into potential losses and risk appetite, and effectively communicate findings to stakeholders
• Collaborate with cross-functional teams, stakeholders to analyse and manage Cyber risk exposures, while also exploring and assessing other emerging risks
• Prepare reports, presentations, and communicate complex actuarial concepts to both technical and non-technical audiences, including senior management and external stakeholders
• Continuously enhance technical expertise, keeping up to date with actuarial standards, industry best practices, and emerging actuarial techniques
• Communicate the solution, its parameters, its assumptions and its inner workings to audiences who vary widely in their levels of technical fluency and seniority

What you need to have:

The candidate must possess the following attributes:

• We're looking for someone with 5 to 8 years of experience building statistical models and associated data architectures
• 5+ years Actuarial experience with a pricing background or reserving
• A degree in Statistics/Mathematics/Actuarial/Computer Science/Engineering
• Preferably part qualified Actuary. Preferable papers (CS1, CS2, SP7, SP8, SA3)
• Detailed knowledge of actuarial pricing techniques
• Detail orientation, communication, and interpersonal skills
• Excellent Microsoft Office skills, particularly in Excel (including VBA)
• Strong problem-solving skills with an emphasis on research & product development
• Knowledge and demonstrated experience of advanced statistical techniques, concepts, and applications - Stochastic Modelling, GLM/Regression, Random Forest, Boosting, Trees, Text Mining, Social Network Analysis, etc.
• Ability to apply and advise on state-of-the-art advanced analytic and quantitative tools and modelling techniques to derive business insights, solve complex business problems, and improve decisions
• Expert level proficiency in statistics and intermediate level proficiency in computer languages like Python, R, SQL, etc.
• A drive to learn and master new technologies and techniques
• Excellent written and verbal communication skills for coordinating across teams

What makes you stand out

• Strong academic rigour with statistics skills from top tier colleges
• Cyber Risk experience with Insurance would be preferred
• Strong programming skills and technical individual contributor
• Ability to take initiatives to strive for improvement in analytic techniques, processes, and outputs
• Excellent communication and leadership abilities
• Knowledge of Tableau, Power BI or other BI tools will be an added advantage
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks

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.