Marsh & McLennan Companies, Inc.
Marsh is a global leader in insurance broking and risk management. In more than 130 countries, our experts in every facet of risk and across industries help clients to anticipate, quantify, and more fully understand the range of risks they face. We work with clients of all sizes to define, design, and deliver innovative solutions to better quantify and manage risk. We offer risk management, risk consulting, insurance broking, alternative risk financing, and insurance program management services to businesses, government entities, organizations, and individuals around the world. To every client interaction we bring an unmatched combination of deep intellectual capital, industry- specific expertise, global experience, and collaboration.
Since 1871, clients have relied on Marsh for trusted advice, to represent their interests in the marketplace, make sense of an increasingly complex world, and help turn risks into new opportunities for growth. Our more than 30,000 colleagues work on behalf of our clients, who are enterprises of all sizes in every industry worldwide. We embrace a culture that celebrates and promotes the many backgrounds, heritages and perspectives of our colleagues and clients. Visit www.marsh.com for more information and follow us on LinkedIn and Twitter @MarshGlobal
This position is for an intern in Data Science who, under close supervision, develops quantitative models and statistical analyses for insurance risk modeling. This position assists in research of economic factors, performs a variety of basic financial and statistical analysis and supports the development of new, market-leading analytics-based tools to help clients assess and mitigate risk.
- Assists in the development of new, market-leading analytics-based tools to assess risk
- Performs basic quantitative modeling and statistical analysis in order to assess risk and viability of risk mitigation solutions
- Supports the understanding of business problems with the broader goal of creating an approach that starts with determining structured and unstructured data needs and availability, builds predictive and/or Machine Learning models, and finalizes with results that unlock insight for clients and colleagues
- Demonstrates statistical analysis skill, data mining, actuarial, and/or research techniques, combined with broader awareness of the business and ongoing research, to function in a collaborative and consultancy role
- Applies basic understanding of product and risk assessment and possible outcomes by scenario testing
- Supports team members in designing analytical models and processes to help internal and external clients quantify and mitigate risks
- Pursuing graduate degree in Math, Statistics, Actuarial Science or related field
- Interest in pursuing designation from the Casualty Actuarial Society preferred
- Location: New York, NY
- Ability to explain facts and figures related to job area
- Developing statistical modeling knowledge
- Detail orientation, communication, and interpersonal skills
- Knowledge of programming languages such as Python, R, SAS, VBA a plus
- Microsoft Office skills, particularly in Excel (including Visual Basic) preferred