Quant Scientist (Remote, US-Time Zone)

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, data analysis, and working with ML-driven workflows.
• Experience interpreting, validating, or stress-testing quantitative or machine learning models (e.g., backtesting, scenario analysis, or model diagnostics).
• Ability to bridge finance and technology: translate investment concepts into technical requirements and challenge model outputs using real-world financial intuition.
• Strong analytical mindset with the ability to communicate complex quantitative insights clearly to both technical and business stakeholders.
• Fluent in English (written and spoken).

‍

Bonus Points

• Solid understanding of Git-based workflows (branching, code reviews, version control) in collaborative research or production environments.
• Experience leveraging LLMs and AI coding tools (e.g., Claude Code, GitHub Copilot) to accelerate prototyping, refactor code, and optimize algorithmic performance.
• Proven ability to thrive in high-pressure, collaborative environments, delivering precise results under tight market-driven or project deadlines

‍