ab sofort

🎓 Master Thesis Opportunity | Venture Capital & Data Science

We believe many of the most promising companies are not fundraising. They’re profitable, focused, and flying under the radar.

We’re looking for a Master’s student to explore how successful startups actually scale — and how early signals of that success can be identified before companies show up in VC deal flow.

The thesis will focus on:

Analyzing successful startups & scale-ups
Extracting patterns, KPIs, and early growth signals
Building a data-driven model to identify scalable, bootstrapped companies

💡 Paid thesis | Real VC use case
📍 Munich preferred, remote possible
📆 Start flexible (2026)

If you’re curious about venture capital, data, and what truly makes companies succeed — let’s talk.

📩 DM me or reach out via EMAIL

🔹 2️⃣ University Career Portal Version (clear, formal, concise)

Master Thesis (m/f/d)

Data-Driven Identification of Scalable Startups | Venture Capital

Location: Munich (preferred) or remote
Start: Flexible (2026)
Compensation: Paid

Description:
We are a venture capital fund focused on backing scalable B2B technology companies. For a Master’s thesis, we are seeking a student to research how successful startups scale and how early indicators of scalable success can be identified in bootstrapped companies that are not actively fundraising.

The thesis will involve analyzing growth patterns, structures, and KPIs of successful startups and developing a data-driven or data-supported framework to identify similar companies at an early stage.

Your profile:

Master’s student in Data Science, Business Analytics, Entrepreneurship, Computer Science, Economics, or a related field
Strong analytical skills and interest in startups and venture capital
Ability to work independently in a research-driven, practical environment

What we offer: