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About the Role
You'll join the Equity Selection team, which builds machine-learning models to forecast relative stock returns. Your focus will be the alpha signals that power these models — work that combines research, economic intuition, and engineering. We care not only about finding signals that work, but also about understanding why they work. This is hands-on work: what you build drives our live strategies.
Responsibilities
- Build and evaluate individual signals, with scope growing over time.
- Search for and evaluate signals across datasets and investment universes, assessing statistical and economic performance.
- Implement alpha signals by transforming raw data into robust signals within a feature computation graph, avoiding look-ahead bias.
- Construct composite signals by combining correlated signals, weighting them by uniqueness and information content.
- Automate the research loop using LLM/agentic tooling for signal discovery, experiment grids, and report generation.
Requirements
- Master's degree or PhD in a quantitative field (mathematics, physics, computer science, financial engineering, statistics, or similar).
- Solid grounding in statistics and working knowledge of econometrics.
- Ability to reason about noisy real-world data.
- Familiarity with collaborative Python development (Git, code review).
- Ability to write maintainable, well-tested code (Pydantic, pytest).
- Experience manipulating data with Polars or pandas.
- Strong interest in financial markets and quantitative investment processes.
- Team-oriented mindset and preference for in-office collaboration.
Skills
- Python development
- Git
- Code review
- Pydantic
- pytest
- Polars
- pandas
- LLM/agentic tooling
- scikit-learn
- LightGBM
- PyTorch
- numerical libraries
- statistical libraries
- MLOps libraries
- SciPy
- statsmodels
- MLflow
Location
- Berlin
Work Type
- In-office collaboration
Experience Level
- Mid-level
Education Level
- Master's degree
- PhD
Benefits
- Mentorship from senior researchers and engineers
- Early ownership of work
- Internal workshops
- Team events
- Urban Sports Club membership
- Access to Corporate Benefits
- Healthy food and drinks
- Apple hardware
About the Company
- Ultramarin is a quantitative asset manager in Berlin.
- We run systematic equity (long-short and long-only) and asset-allocation strategies in developed markets.
- We are a Deep-Tech pioneer offering AI-based investment solutions.
- We leverage machine learning for sustainable capital market investments, building on quantitative asset management best practices.
- Our interdisciplinary team includes experts in Finance, Computer Science, Software Engineering, Machine Learning, Mathematics, Physics, and Neuroscience.
- Ultramarin collaborates closely with leading universities and is part of the global AI community as a member of Inquire Europe.
- We are a pioneer in AI-based analysis and decision-making in asset management.
- Founded in 2017, Ultramarin is headquartered in Berlin with additional locations in Frankfurt and Munich, supported by leading international business angels and VCs.