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
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Degree in finance, quantitative finance, financial engineering, mathematics or related field; solid Python/Java skills; experience with financial modeling, data analysis, ML workflows; ability to interpret and validate quantitative models; fluent English.
Key Responsibilities
- evaluating model outputs
- translating research signals
- designing quantitative models
Skills & Tools
Python, Java, Git, Claude Code, GitHub Copilot
Job Details
- Category: Data and Analytics
- Seniority: Mid Level
- Commitment: Full Time
- Workplace: Remote — United States
- Languages: English
About MDOTM
A financial technology company bridging quantitative modeling and real-world financial applications. — Industry: Finance