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About MDOTM
MDOTM is the Global leader in AI-driven investment solutions. Founded in 2015, we earned significant recognition in 2017 as the only European fintech startup selected by Google for its acceleration program in Silicon Valley.
Since then, we have been growing continuously, establishing a strong international presence with offices in London, Milan and New York.
If you are looking for a fast-paced environment and are willing to take ownership, this is the right opportunity for you!
Role Overview
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 Why Join Us?
Work at the leading edge of technology, leveraging our decade of experience in proprietary AI to build the next generation of industry-defining tools.
Competitive salary & trulyflexible work environment.
Benefit from an unlimited learning and development budget to stay at the bleeding edge of AI research, alongside a fast-track path into technical leadership or principal research roles.
Collaborate daily with anultra-international team(18+ nationalities) spread across our offices in Milan, London and New York.
Annualcompany retreatat a stunning location.
Fast-trackcareer progression, with opportunities to grow into leadership roles.