As the asset manager of Munich Re and ERGO, MEAG makes a significant contribution to the success of Munich Re Group. Our staff brings together peerless know-how in all relevant asset classes and acts as the driving force behind our success as one of the world’s top asset managers.

We are seeking a talented and motivated Financial Data Engineer / Software Developer (m|f|d) for our Central Quant Team. You will be shaping our analytical data platform for Public Markets by working at the intersection of portfolio management, data engineering, and IT, driving innovation, automation, and analytical excellence to support our investment process value chain. We’re looking for a hands-on, technically skilled candidate with a passion for clean code, smart data handling, and the ability to collaborate across diverse teams.

## **Your main responsibilities:**

- Responsible for the Public Markets Analytical Data Platform as central location for portfolio management specific data and analytical tools
- Develop and maintain analytical tools, workflows, and data pipelines for Public Markets teams on our analytical data platform
- Drive standardization in coding practices, tool development, and data architecture
- Design data models for structured and unstructured data (e.g., APIs, JSON feeds, CSVs, vendor data)
- Support portfolio managers in prototyping new analytical tools and visualization applications
- Automate workflows, ensure transparency and documentation of implemented analytical tools
- Collaborate closely with the Market Data team and Munich Re IT to ensure high-quality data sourcing, validation, and to build scalable, production-ready solutions

## **Your profile:**

- Master’s degree or PhD in computer science, data science, statistics, or a related field (e.g. Mathematics, Physics, Engineering, or Finance)
- Strong programming skills in Python (must-have) with focus on clean, testable, production quality code; experience in SQL, R, or C++ is a plus
- Experience with Databricks and Apache Spark, Azure DevOps, and Git or similar applications
- Familiarity with PowerBI, MS Excel, dashboarding tools and machine learning libraries in Python (e.g., PyTorch, Scikit-learn)
- Structured thinking and problem-solving skills with hands-on and solution-oriented mindset
- Deep understanding of time series and cross-sectional data structures
- High level of accountability and ownership especially for code quality, data structure, and workflow design
- Solid understanding of capital markets and financial instruments ideally in the context of asset management supplemented by understanding of machine learning and probability theory
- Proficiency in time series analysis, portfolio analytics, and risk metrics
- Strong communication skills and ability to translate quant ideas into business impact
- Business proficiency in English (C1), German is a plus

## **Benefits:**

- **Flexibility: **Mobile work (option to work from home a few days a week), 30 days of vacation
- **Asset Accumulation & Retirement Planning:** Company pension system & employee savings plan
- **Development:** Intensive professional & personal development (internal & external offerings), LinkedIn Learning access
- **Health:** Comprehensive company doctor services, Urban Sports cooperation
- **Family:** pme family service, childcare allowance, care assistance, cooperation with daycare centers, flexible working hours
- **Other:** Daily free lunch in our cafeteria, Free hot drinks & water, "Deutschland Ticket Job" subsidy, Events, Underground parking garage with e-charging infrastructure & much more!

\*Please note that this list is based on current collective agreements. These may change. The list is for information purposes only. We do not accept any liability for individual points. 

MEAG stands not only for a partnership-based relationship with customers, but also for fair treatment of applicants and employees. Regardless of gender. So if we use the masculine form of personal designations, this is purely for the sake of readability. Applicants with disabilities will be given preferential consideration if they are otherwise essentially equally qualified.