Quantitative Finance Intern - Fintech

StrategyBridgeAI; München; Hybrid; EUR 13.000 - 22.000; Teilzeit

Benefits dieser Stelle

Relocation assistance

Company apartment in Munich

Hybrid work setup

Wellpass

Team events

Tax-free benefits

Zusammenfassung

StrategyBridgeAI is seeking a Quantitative Finance Intern to bridge engineering and finance, bringing financial data into production and turning it into automated analyses.

You will evaluate new data sources, implement valuation logic, KPIs and benchmarking, and take ownership of output quality for expert review.

Qualifikationen

• Motivation and ownership of a founder mindset; own problems end-to-end.
• Corporate finance foundation: read P&L, balance sheet, cash flow.
• Proficiency in Python and working with messy data.
• Strong interest in quantitative work: econometrics, statistics, data-led insights.
• Experience end-to-end data pipelines: from API/files to analysis.
• Use of AI/LLM tools with ability to audit outputs and maintain quality.
• Strong communication and structured problem-solving skills.

Aufgaben

• Bridge engineering and finance teams to bring financial data into production.
• Translate corporate finance methods into automated analyses: valuations, KPIs, benchmarking.
• Take ownership of output quality; ensure numbers hold up for experts.

Kenntnisse

Python

Data analysis

Communication

Problem solving

Ownership mindset

AI/LLM tools

Quantitative methods

Tools

Apache Spark

Kafka

Dagster

Airflow

Jobbeschreibung

We're setting new standards in corporate finance. With a focused team of 30 — one in four of us a former founder — we combine deep expertise in finance, data science and AI to build THE platform for deal & advisory teams, strategy departments, auditors and banks. We're one of the fastest-growing startups in the DACH-region and now scaling internationally. Our ambition is clear: to set the global standard.

Our Culture

• Ownership. You own your topics end to end, from idea to shipped.
• Strong opinions, loosely held. We argue hard about the right solution, then commit together.
• Simple beats clever. The simplest thing that solves the problem wins. We'd rather ship clear code than impressive code.
• Leave it better than you found it. Speed is a priority, but we don't trade it for technical debt that kills future velocity. We build simple, modular systems that are easy for the next person (or future you) to understand.
• Mistakes are a gift. We make mistakes and learn from them. The one thing we avoid is making the same one twice.
• Serious about the work, not about ourselves. We take our goals seriously, ourselves less so.

The role: Quantitative Finance Intern

Small team, high bar. You'll be the bridge between our engineering and finance teams — getting the financial data our platform runs on into production and making sure it holds up, then turning it into automated analyses. Over six months you'll work on the same codebase and the same roadmap as the rest of the engineering team. Your responsibilities will include:

• Research and evaluate new data sources: company registers, filings, market and transaction data — and judge what they're actually worth for an analysis.
• Get new data into production — from the raw source to something deal teams can actually work with.
• Translate corporate finance methods into automated analyses: valuation logic, KPIs, peer benchmarking, financial statement analysis.
• Take ownership of output quality — the numbers we ship have to hold up in front of an expert.

Qualifications

- to be successful in this role, you will need:

Must-haves

• We expect the motivation and ownership of a founder. You own problems end-to-end and care more about the user outcome than your ticket description.
• Corporate finance foundation — you read a P&L, balance sheet and cash flow statement without help, and you know the standard valuation approaches.
• Proficiency in Python. You write code others can read and you're comfortable with messy real-world data.
• Proven interest in quantitative work — econometrics, statistics, stochastic processes — and experience working with large sets of data.
• You've taken data end to end — pulled it from somewhere (an API, a scraper, a database, a pile of files), cleaned it up, and built something on top.
• You use AI/LLM tools to move faster, but you have the technical depth to audit their output and maintain high code quality. No "AI slop".
• Strong communication and structured problem-solving skills.

Nice-to-haves

• Professional experience in investment banking, private equity, audit, corporate finance or similar.
• Own projects. Something you built outside of coursework or a job.
• You've worked with financial or company data, like filings, registers or transaction data.
• Experience with big data technologies (e.g. Apache Spark, Kafka) & data orchestration tools (e.g. Dagster, Airflow).
• API and service design, clean enough that someone else can build on it.
• You've used LLMs to extract structured data from unstructured documents.

Not sure you tick every box? Apply anyway. We care more about ambition and how fast you learn than about a complete checklist.

What we offer

• Responsibility from day one: flat hierarchies, fast decisions, and the room to actually shape the product. You won't be boxed into one corner of the stack.
• Permanent Employment: strong interns are the first people we talk to about a full-time role.
• Learning curve: one of the steepest you’ll find in Germany. Not an empty claim — ask the team.
• People: Build with experts from Big Tech, Silicon Valley, Investment Banking, and Hedge Funds.
• Setup: Munich, hybrid. Modern office, EGYM Wellpass, team events, tax-free benefits.
• Relocation: company apartment in Munich available on request.

Language

English is our company language; German is nice to have.

Hiring process

We’re an equal-opportunity employer. This role is open to all genders (m/f/x). We value diverse backgrounds and perspectives and welcome applications from all qualified candidates.