Risk Modeling Analyst
hace 1 mes
Marsh McLennan is the worldâs leading professional services firm in risk, strategy, and people through the business units: Marsh, Mercer, Guy Carpenter and Oliver Wyman.
At Marsh we offer consulting and risk management services, insurance brokerage and insurance program management for different sectors of the economy and therefore we are now looking for candidates for the following position located in Bogota.
Risk Modeling Analyst
What can you expect?
- Relationship with internal teams at Marsh McLennan.
- Work within the HUB IKS - India Knowledge Services.
- Works with India.
- Relationship and work in English and Spanish.
Whatâs in it for you?
- Life insurance.
- Personal Accident insurance.
- Health insurance
- Vacation bonus
- Christmas Bonus
- Hybrid work (office and home)
- Among others
We will count on you to:
- Help establish and implement new, market-leading analytics-based tools to assess and mitigate risk
- Develop complex models 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 minimize manual intervention.
- Estimate technical prices and come up with layer efficiency for different insurance layers
What you need to have:
- 2+ years of experience in Risk analysis. Preferable in insurance background knowledge.
- A degree in Statistics/Mathematics/Actuarial/Engineering.
- Power BI proficiency.
- Good programming language skills on Python or R.
- Excellent Microsoft Office skills, particularly in Excel (including VBA) and PowerPoint
- English proficiency.
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
Marsh is the worldâs leading insurance broker and risk adviser. With more than 45,000 colleagues advising clients in over 130 countries, Marsh serves commercial and individual clients with data-driven risk solutions and advisory services. Marsh is a business of Marsh McLennan (NYSE: MMC), the worldâs leading professional services firm in the areas of risk, strategy and people. With annual revenue of $23 billion, Marsh McLennan helps clients navigate an increasingly dynamic and complex environment through four market-leading businesses: Marsh, Guy Carpenter, Mercer, and Oliver Wyman. For more information, visit marshmclennan.com, follow us on LinkedIn and X.
Marsh McLennan is committed to creating a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, disability, ethnic origin, family duties, gender orientation or expression, 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 âanchor dayâ per week on which their full team will be together in person.
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