Engagement Lead – Risk Consulting/ CONSULT MGR I

Marsh McLennan•New York, NY

10d•Hybrid

About The Position

Marsh USA LLC is seeking candidates for the following full-time position based in the New York, NY office (A telecommuting/hybrid work schedule may be permitted within a commutable distance from the worksite, in accordance with company policies.) Engagement Lead – Risk Consulting/ CONSULT MGR I We will count on you to: Work on enterprise-wide risk analytics, data strategy, and digital transformation initiatives. Design and execute complex, multi-dimensional data analyses to generate transformative insights, support strategic decision-making, and inform industry benchmarks. Lead cross-functional projects with limited oversight, supporting innovation and advancing data maturity across the organization. Develop scalable and sustainable solutions that leverage cutting-edge technologies such as deep learning, artificial intelligence, automation, and real-time analytics. Drive measurable business impact through improved risk management, underwriting, claims optimization, and enterprise risk quantification. Carry out expertise in advanced statistical modeling, machine learning, artificial intelligence (AI), and data engineering, with a proven track record of deploying these techniques to address challenges in the risk and insurance domain. Offer data-driven insights that support enterprise risk strategy, product development, and operational improvement. Contribute to the development and implementation of comprehensive data strategy frameworks integrating them into holistic risk management architectures, insurance analytics ecosystems, and strategic planning efforts. Serve as a trusted advisor to C-suite executives and board members, translating complex data insights into actionable strategies that support organizational growth and resilience. Support high-level discovery initiatives, facilitate strategic workshops, and conduct executive interviews to identify latent data opportunities, define future-state data architectures, and build roadmaps for digital transformation and ongoing data maturity. Maintain strong technical proficiency in tools such as Python, R, SAS, Tableau, Power BI, and cloud-based analytics platforms. Build scalable, automated analytics pipelines to support enterprise-level decision-making. Provide strategic guidance on RMIS architectures, vendor solutions, and integration strategies. Lead enterprise-wide RMIS modernization initiatives, manage vendor negotiations and implementation processes, and ensure alignment with organizational risk appetite and compliance requirements. Contribute to industry thought leadership through research publications, conference presentations, and mentorship, promoting innovation and continuous learning within the team. Build toward future growth of risk management through data-informed insights and analytics-driven transformation.

Requirements

Must have a Bachelors degree or foreign equivalent in Business Intelligence & Analytics, Computer Engineering, or a related field plus four (4) years of experience in the position offered or a related position.
Must have four (4) years of experience with all of the following: Utilizing intelligence and analytics in property and casualty insurance to support claims processes related to workers’ compensation, general liability, and automobile liability; Designing and creating business analytics and reporting tools to improve processes and support informed client decision-making; Developing a comprehensive understanding of data strategy frameworks, with a focus on their application to enterprise risk management, insurance analytics, and strategic decision-making processes; Conducting sophisticated, high-impact data analyses with a high degree of accuracy and consistency, leading complex projects with minimal oversight; Utilizing data manipulation libraries and visualization tools, including Power BI, Tableau, and RShiny, to analyze and present data effectively; Implementing machine learning algorithms and frameworks using TensorFlow, Keras, and RShiny to develop predictive models and enable data-driven decision-making; Cleaning, transforming, and preparing data from multiple sources to ensure suitability for analysis; Leveraging big data tools and frameworks, including AWS and Spark, for processing and analyzing large datasets; Possessing deep technical expertise within specialized domains, including advanced statistical modeling, machine learning, and data engineering techniques relevant to risk and insurance; Collaborating in cross-functional teams, working with data professionals, engineers, and business stakeholders; Programming in languages including Python and R for modeling and analysis; and Programming in SQL for database management and data manipulation.

Responsibilities

Work on enterprise-wide risk analytics, data strategy, and digital transformation initiatives.
Design and execute complex, multi-dimensional data analyses to generate transformative insights, support strategic decision-making, and inform industry benchmarks.
Lead cross-functional projects with limited oversight, supporting innovation and advancing data maturity across the organization.
Develop scalable and sustainable solutions that leverage cutting-edge technologies such as deep learning, artificial intelligence, automation, and real-time analytics.
Drive measurable business impact through improved risk management, underwriting, claims optimization, and enterprise risk quantification.
Carry out expertise in advanced statistical modeling, machine learning, artificial intelligence (AI), and data engineering, with a proven track record of deploying these techniques to address challenges in the risk and insurance domain.
Offer data-driven insights that support enterprise risk strategy, product development, and operational improvement.
Contribute to the development and implementation of comprehensive data strategy frameworks integrating them into holistic risk management architectures, insurance analytics ecosystems, and strategic planning efforts.
Serve as a trusted advisor to C-suite executives and board members, translating complex data insights into actionable strategies that support organizational growth and resilience.
Support high-level discovery initiatives, facilitate strategic workshops, and conduct executive interviews to identify latent data opportunities, define future-state data architectures, and build roadmaps for digital transformation and ongoing data maturity.
Maintain strong technical proficiency in tools such as Python, R, SAS, Tableau, Power BI, and cloud-based analytics platforms.
Build scalable, automated analytics pipelines to support enterprise-level decision-making.
Provide strategic guidance on RMIS architectures, vendor solutions, and integration strategies.
Lead enterprise-wide RMIS modernization initiatives, manage vendor negotiations and implementation processes, and ensure alignment with organizational risk appetite and compliance requirements.
Contribute to industry thought leadership through research publications, conference presentations, and mentorship, promoting innovation and continuous learning within the team.
Build toward future growth of risk management through data-informed insights and analytics-driven transformation.