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Quant Scientist

Pubblicato il 17-08-2026 - MDOTM in Milano

We are looking for a Quantitative Data Scientist to join our Research and Development Team in Milan. This is a critical, high-impact hire designed to be the bridge between complex quantitative modeling and real-world financial application.

The ideal candidate combines a strong financial intuition with a /"hands-on/" attitude. You will be responsible for translating business needs into technical solutions, ensuring our investment strategies are robust, scalable, and aligned with client expectations. You will serve as a key integrator across research, and investment functions, bringing order to innovation.

Key Responsibilities
- Critically evaluate ML model outputs to ensure alignment with financial theory and real-world market dynamics, while accounting for client-specific objectives, constraints, and investment frameworks.
- Translate research signals into actionable investment strategies and portfolio construction frameworks.
- Collaborate with ML researchers to refine models, incorporating financial domain expertise and contributing to model design where needed.
- Design,



prototype, and scale quantitative models using Python and Java, maintaining a high standard for code quality and modularity.
- Contribute to the financial validation layer of the R&D; cycle by developing and maintaining test frameworks that identify inconsistencies and support continuous model improvement.
- Translate complex portfolio objectives into rigorous, testable modeling specifications that bridge the gap between investment intent and algorithmic execution.
- Collaborate across technical workstreams to ensure research outputs are aligned with investment objectives and successfully integrated into production workflows.

Requirements
- Degree in Finance, Quantitative Finance, Financial Engineering, Mathematics, or a related field.
- Understanding of portfolio construction, asset allocation, and risk management
- Solid Python/Java programming skills, with experience in financial modeling, d

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