Master Thesis in the field of Investment Management

Job Description:

In order to support the integration of AI in Operations Investment decisions, Airbus Operations is looking for a

Master student (d/f/m) in the field of Investment Management

title of thesis: Generative AI & Process Automation in Industrial & Strategic Investment/CapEx Decisions

You are looking for a master thesis and want to get to know the work of an Investment Manager in Industrial Operations? Then apply now! We look forward to you supporting us in the central Capex Management department as a master student (d/f/m)!

• Location: Hamburg
• Start: Q1 2027
• Duration: 6 months

Your location

You will be working at the largest production site for civil aircraft situated in Hamburg. Its location on the southern banks of the river Elbe includes the option to commute by ferry. Experience the special flair of Hamburg in your spare time where vibrant cosmopolitan culture meets nautic legacy.

Your benefits

• Work-life balance with a 35-hour week (flexitime).
• International environment with the opportunity to network globally.
• Work with modern/diversified technologies.
• At Airbus, we see you as a valuable team member and you are not hired to brew coffee, instead you are in close contact with the interfaces and are part of our weekly team meetings.
• Opportunity to participate in the Generation Airbus Community to expand your own network.

Your tasks and responsibilities

As-Is Process Mapping:

• Assess the current state of the end-to-end CapEx dossier creation lifecycle across operational sites. You will have a close exchange with the results of the VS (Value Stream Assessments) results.

Optimisation Analysis:

• Pinpoint bottlenecks, redundant reporting between local presentations and our enterprise CapEx Planning Tool (CPT), and root causes in heavy 27-slide dossiers

Solution Design:

• Outline proposed improvements by architecting an intake and generation pipeline connecting Google Drive, Gemini AI, and Google Slides to condense content into a decision-oriented 7-slide format and and integrate “investment intelligence”, e.g. benchmarking or cost referentials.
• Design, test, and calibrate prompt or similar tools workflows for Gemini to synthesize executive summaries, risk matrices, and multi-year cash phasing projections.

Pilot Case:

• Test your approach by running 1 to 3 live industrial investment dossiers through the automated pipeline.

Performance Comparison & AI Compliance:

• Evaluate KPI improvements (As-Is vs. To-Be), measuring administrative time savings and controller approval speeds and general compliance.

Desired skills and qualifications

• Enrolled fulltime in the final year of a Master’s degree (Bac+5 / MSc) in Industrial Engineering, Information Systems (with strong business/operations interest), Business Analytics, Data Science, or a related dual engineering/business program.
• Technical Mindset: Strong interest in Generative AI prompting, workflow automation, and low-code integration (e.g., Google Workspace ecosystem, Apps Script / Python, API interactions).
• Business & Financial Curiosity: Comfortable understanding operational investment concepts (CapEx vs. OpEx, cash phasing, business cases, ROI/NPV logic).
• Communication & Change Leadership: Strong interpersonal skills to interface smoothly with diverse stakeholders (from shop-floor industrial engineers to financial controllers).
• Language Proficiency: Negotiation-level fluency in English (working language). Knowledge of French, German, or Spanish is an asset.

Please upload the following documents: cover letter, CV, relevant transcripts, enrollment certificate.

Not a 100% match? No worries! Airbus supports your personal growth.

Take your career to a new level and apply online now!

This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth.

Company:

Airbus Operations GmbH

Employment Type:

Final-year Thesis

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Experience Level:

Student

Job Family:

Support to Management <JF-FA-ES>

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