Marsh McLennan

Marsh McLennan

Summer Intern, Master's Finance Innovation & Technology (FIT)- New York, 2027

New York - 1166 · Intern · Internship

Sponsorship not specifiedDetected 2 days ago
PythonSpringSQLLinuxData AnalysisData ScienceCommunicationCollaborationProblem SolvingAdaptability

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odds of building a lasting career here

34Risky
Cap-exempt (no lottery)0
Sponsors this role70
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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About the role

  • Marsh is a global professional services firm offering clients advice and solutions in the areas of risk, strategy, and people.
  • With over 95,000 colleagues worldwide and a market capitalization of $81 billion, we provide analysis and advice to clients in more than 130 countries.
  • Employees will gain hands-on experience working within one of our Finance groups.

Requirements

  • Ability to translate business problems into technical solutions using data, automation, and analytics
  • Collaborative communication skills and the ability to work effectively across technical and non-technical teams
  • Self-starter mindset with the ability to produce high-quality work with minimal direction
  • Agility, adaptability, and the ability to learn quickly in a fast-paced environment

Nice to have

  • Pursuing a Master's degree in Computer Science, Data Science, Information Systems, Engineering, or a related technical field, with an expected graduation date on or before Spring 2028
  • Ideally you will have 2-3 years' work experience prior to obtaining your master's degree
  • Advanced knowledge of programming languages such as SQL, Python, or similar for data analysis and project development
  • Familiarity with operating systems such as Windows and Linux
  • Interest in analytics, automation, modeling, and technology-enabled finance solutions
  • Experience with data analysis, process automation, or software development is preferred
  • You must have legal authorization to work in the U.S. on a permanent basis without the need for sponsorship now or in the future

Compensation

  • With annual revenue of over $27 billion and more than 95,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective.

Company info

  • Description:
  • 2027 Summer Finance Innovation & Technology (FIT) Program
  • Are you interested in developing innovative solutions to complex finance issues?
  • Would you like to implement tools and technology to improve efficiency and accuracy in finance?
  • Are you a proactive problem-solver interested in partnering with cross-functional teams to deliver results and insights to key stakeholders?
  • The Finance Innovation & Technology (FIT) Program offers a challenging opportunity to students to develop technology solutions for finance.
  • In addition, Finance Innovation & Technology participants can utilize our online learning platform, Finance Academy, to enhance their technical and professional skills.
  • Intellectual curiosity and strong interest in finance, technology, and innovation
  • Strong problem-solving skills with a detail-oriented and structured approach
  • The applicable hourly rate for this role is $40.
  • The hourly rate offered will be determined on factors such as experience, skills, training, location, certifications, and education.
  • Decisions will be determined on a case-by-case basis.
  • Marsh (NYSE: MRSH) is a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries.
  • With annual revenue of over $27 billion and more than 95,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective.
  • For more information, visit marsh.com, or follow us on LinkedIn and X.
  • Marsh is committed to embracing a diverse, inclusive and flexible work environment.

Visa & Work Authorization

  • You must have legal authorization to work in the U.S. on a permanent basis without the need for sponsorship now or in the future
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This listing is sourced directly from Marsh McLennan's careers page and normalized into a canonical job model.