Internship

Data Strategy Analytics Engineering Co-op

College Program 2025

Confirmed live in the last 24 hours

Marsh & McLennan

Marsh & McLennan

Compensation Overview

$30/hr

Company Does Not Provide H1B Sponsorship

New York, NY, USA

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.

Category
Data Science
Data Engineering
Data & Analytics
Required Skills
Scikit-learn
Python
R
SQL
Machine Learning
Data Analysis
Excel/Numbers/Sheets
Requirements
  • Pursuit of Masters or Bachelor’s degree in a technical field (statistics, computer science, data science or related quantitative field) or a demonstrated ability to learn new analytical concepts quickly.
  • Strong academic record in major and experience is more important than the field of study.
  • Excellent verbal and writing skills for complex communications with Guy Carpenter colleagues at all levels of the organization.
  • Exposure to technologies and programming languages such as Python, R, SQL, Scikit-Learn, machine learning.
Responsibilities
  • Perform exploratory data analysis, develop or enhance machine-learning models to support Data Strategy products, and provide conclusions and recommendations that show a high level of critical thinking.
  • Assist in the collection, cleaning, and analysis of large datasets related to reinsurance operations.
  • Collaborate with cross-functional teams to gather requirements and understand product needs.
  • Develop and generate reports and dashboards to communicate findings to stakeholders.
  • Participate in product testing and data validation to ensure accuracy and reliability of analytics solutions.
  • Consume data from a variety of sources (relational DBs, APIs, NetApp, and other cloud storage, FTPs) & formats (Excel, CSV, XML, parquet, unstructured)
  • Construct and maintain data pipelines between internal/external sources and the data lake and implement modern quality assurance practices including automated validation with frameworks like dbt or Great Expectations.
  • Participate in development standards across the team through code reviews, unit/integration testing, and monitoring.
Desired Qualifications
  • Prior experience with strong analytical skills and intellectual curiosity as demonstrated through academic experience or work assignments.
  • Experience working in an Agile environment to facilitate the quick and effective fulfillment of group goals.
  • Experience with risk evaluation modeling and/or building data products.
  • Software best practices including DRY coding, unit & integration testing, documentation, etc.
  • Developing in a modern, agile SDLC environment (dev/qc/prod environments with CI/CD, etc.) using a cloud environment (AWS/GCP/Azure).
  • Consuming REST APIs.
  • Good interpersonal skills for establishing and maintaining good internal relationships, working well as part of a team and for presentations contribute to both technical and non-technical discussions.
  • Strong emphasis on a desire to learn quickly and add value to team initiatives.

Company Size

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Company Stage

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Total Funding

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Headquarters

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Founded

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