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Data Analytics Internship

Braun Management

Remote · 全职

抢先申请

经验
任何
薪水
职位空缺
1
发布
1 小时前
Work mode
在家办公
学历
Mathematics, Statistics, Economics, or related analytical field
Eligibility
Candidates with an analytical academic background such as mathematics, statistics, economics, or a related field, and the ability to work effectively in a fully remote, asynchronous environment, are suitable for this role.
Resume
Required to apply

职位描述

About the company

Braun Management helps organizations address internal structure issues that slow down progress in complex European business environments. The team uses evidence-based analysis to help leadership teams understand underperformance and make clearer decisions about roles and responsibilities.

Role overview

In this remote Data Analytics Internship, you will support an important assignment for a major German logistics and infrastructure company. The client oversees a large asset portfolio and needs better insight into operational bottlenecks across supply chain and maintenance functions. Your main contribution will be turning scattered data into clear written findings that consultants can use to support executive decision-making.

Key responsibilities

  • Pull data from different logistics and asset management platforms, then clean and validate it so the outputs are dependable.
  • Look for trends linked to delays, inefficiencies, and resource distribution issues within the client’s infrastructure network.
  • Draft organized reports that communicate your findings to senior consultants.
  • Help build simple performance models that make accountability across business units easier to understand.
  • Keep internal process notes up to date so the analytical work can be repeated and reviewed easily.
  • Support basic visual dashboards or charts that present complex issues clearly to executive readers.
  • Work with the consulting team through asynchronous communication tools and refine the analysis using qualitative client input.

What we are looking for

  • Working knowledge of data analysis tools such as Excel, SQL, or beginner-level Python for data handling.
  • Curiosity about how large, complex organizations operate and what drives their internal mechanics.
  • A careful, disciplined approach to cleaning, checking, and verifying data.
  • Strong writing ability with the skill to explain technical results clearly to non-technical stakeholders.
  • Comfort working on your own in a fully remote setup with limited direct supervision.
  • Academic exposure to mathematics, statistics, economics, or another analytically focused field.
  • Willingness to work through incomplete, messy, or difficult data sources.
  • Good organization and time management to handle multiple data tasks within a project timeline.

How we work

The organization works entirely remotely and does not maintain a physical office. Because the team spans multiple time zones and focuses on sensitive organizational issues, communication is heavily written and asynchronous rather than centered on frequent video calls. Clear documentation and logical thinking are highly valued, and team members are expected to record the reasoning behind their conclusions. You will have regular mentor check-ins, while still having the autonomy to manage your own output.

What we offer

This is a paid internship with compensation positioned competitively within the European consulting market. You will gain practical experience on a substantial project for a leading logistics provider and learn more about restructuring and organizational design. A stipend is also provided to support your remote home setup, and the fully remote format comes with a flexible schedule that emphasizes results over fixed desk time. You will be matched with an experienced consultant who will guide you with ongoing feedback and support throughout the internship.

Your work will help the logistics and infrastructure client see the real issues behind day-to-day operations. By preparing accurate, well-structured data, you will help consultants have the difficult conversations needed for structural improvement and create a fact-based path forward for leadership decisions.

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