Magnet.me  -  Het slimme netwerk waar studenten en professionals hun stage of baan vinden.

Het slimme netwerk waar studenten en professionals hun stage of baan vinden.

Knowledge Analyst - Travel, Logistics & Infrastructure Solutions

Geplaatst 19 feb. 2025
Delen:
Werkervaring
1 tot 5 jaar
Full-time / part-time
Full-time
Soort opleiding
Taalvereiste
Engels (Vloeiend)

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Do you want to work on complex and pressing challenges—the kind that bring together curious, ambitious, and determined leaders who strive to become better every day? If this sounds like you, you’ve come to the right place.

Your Impact

As a Knowledge Analyst with TLIS, you will help clients in the TLI sector and beyond to improve operations and make strategic decisions for the future.

In this role, you will provide daily problem-solving, structuring, modeling, and analytical support for our TLIS tools and analyses. You will gather information to develop these tools and synthesize findings into McKinsey-formatted products, such as complex models, summary reports, and standalone presentations for internal and external audiences.​

You will collaborate with other experts, data scientists, IT and software specialists to solve client problems, deepening your knowledge and refining your analytical and thought-partnership skills.​

You’ll have the opportunity to gain new skills and build on the strengths you bring to the firm. You will receive exceptional training as well as frequent coaching and mentoring from colleagues.​

Your Growth

You will be based in our Dusseldorf/Madrid/Amsterdam/Lisbon office, joining theTravel, Logistics & Infrastructure Solutions (TLIS) teampart of McKinsey’s Transportation, Logistics, and Infrastructure practice, delivering technology-enabled consulting services and solutions for our clients.

TLIS combines the most advanced digital tools and techniques along the transport value chain. We enable the deployment and development of a portfolio of McKinsey proprietary solutions required to successfully tackle and solve the complex challenges. Some example solutions include demand modelling, operational benchmarking tools, and network optimization solutions.

Our team of world-class consultants, analysts and data scientists transform data into actionable insights, enabling clients to make well-informed strategic, tactical, and operational decisions. We help organizations capture opportunities, manage risks, and enhance performance.​

Your qualifications and skills

  • University degree in engineering, economics, statistics, physics, software technology or other discipline with a quantitative and programming focus
  • Strong coding capabilities and analytics aptitude; data science, geospatial analytics and experience in modelling large datasets are a plus
  • Experience (internships and/or full-time) in the TLI industry, such ports, shipping, logistics, is a plus
  • Proven ability to collaborate effectively in a team environment and engage with individuals at all organizational levels​
  • Capacity to excel in a fast-paced, results-driven team setting, demonstrating a steep learning curve and a strong commitment to coaching and development​
  • Advanced problem-solving skills with a strong aptitude for working with numbers and quantitative models​
  • Ability to effectively communicate complex ideas in English, both verbally and in writing​; fluency in German is a plus
  • Please review the additional requirements regarding essential job functions of McKinsey colleagues at https://www.mckinsey.com/careers/essential-functions-client-service

Please review the additional requirements regarding essential job functions of McKinsey colleagues.

McKinsey is a global management consulting firm where you'll have unrivaled opportunities to work face-to-face with the leaders of the world’s most impressive organizations and to leave your mark.
We provide a broad range of opportunities for you to meet people, make friends, and build networks that can help you wherever your career takes you

Management Consulting
Amsterdam
Actief in 65 landen
700 medewerkers
50% mannen - 50% vrouwen
Gemiddeld 27 jaar oud