Junior Quantitative Researcher / Developer - Systematic Equity

About the Role

Ultramarin, a quantitative asset manager based in Berlin, specializes in systematic equity strategies including long-short and long-only approaches across developed markets. This position is within the Equity Selection team, which focuses on creating machine-learning models that forecast relative stock returns. The work emphasizes not only generating alpha signals but also comprehending their underlying rationale. This role involves direct hands-on development where your contributions directly impact live investment strategies.

Key Responsibilities

• Identify and assess potential alpha signals by scanning various datasets and investment universes, ensuring robustness through out-of-sample validation and evaluating both statistical and economic merit.
• Develop alpha signals by transforming raw, noisy inputs such as prices, trading volumes, fundamentals, and textual data into stable, parameterized components within a feature computation graph, while avoiding look-ahead biases.
• Create composite signals by consolidating correlated signals into several dependable composites per universe; these are weighted based on uniqueness and informational value, distinguishing true stock selection from inadvertent allocation biases.
• Automate aspects of the research workflow by implementing and using agent-based tools and large language models (e.g., Claude Code), to discover signals, orchestrate experiments, and generate evaluation documentation.

Qualifications and Skills

• Master's degree or PhD in mathematics, physics, computer science, financial engineering, statistics, or closely related quantitative disciplines.
• Strong foundation in statistical analysis and working knowledge of econometrics, enabling sound interpretation of noisy real-world datasets.
• Experience with collaborative software development in Python, including version control tools like Git and code review processes.
• Proficiency in writing maintainable, well-tested code, employing frameworks such as Pydantic and pytest.
• Competence in manipulating and processing data with tools like Polars or pandas.
• Keen interest in financial markets and the quantitative investment methodology.
• A collaborative mindset with a preference for teamwork in an office environment.
• Additional desirable skills: Experience in identifying and assessing alpha signals for systematic or fundamental equity strategies; familiarity with machine learning libraries such as scikit-learn, LightGBM, or PyTorch; knowledge of building and evaluating LLM/agentic tools; and use of scientific and MLOps tools including SciPy, statsmodels, and MLflow.

Why Join Ultramarin?

• Work in a dynamic research atmosphere where ideas evolve quickly from prototypes into production-ready solutions.
• Receive mentorship from experienced researchers and engineers and gain early responsibility for your projects.
• Collaborate within an interdisciplinary team of experts spanning finance, software engineering, and machine learning, emphasizing quality, transparency, and detailed focus.
• Benefit from internal workshops, team events, Urban Sports Club membership, and corporate benefits.
• Work from a modern loft-style office in Berlin’s Prenzlauer Berg district, with access to healthy food options, drinks, and Apple hardware.

About Ultramarin

Ultramarin is a deep-tech pioneer delivering AI-driven investment solutions by leveraging best practices in quantitative asset management alongside machine learning innovations for sustainable investing. The team is composed of specialists in finance, computer science, software engineering, machine learning, mathematics, physics, and neuroscience. Ultramarin maintains close collaborations with leading universities and is a member of Inquire Europe, connecting it to the global AI community. Since its foundation in 2017, the firm has been headquartered in Berlin with additional offices in Frankfurt and Munich, supported by prominent international business angels and venture capitalists.