Quant Scientist

MdotM

Quantitative Data Scientist bridging quantitative modeling and financial application in AI-driven investment solutions. Working with ML models, Python, and Java in a fast-paced environment.

Posted 7/2/2026full-timeRemote • New York • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in financial modeling and quantitative analysis, utilizing Python and Java to develop and validate machine learning models that align with investment strategies and objectives. Strong ability to communicate complex financial concepts and insights to diverse stakeholders.

Highest-signal resume keywords

Financial ModelingQuantitative AnalysisPython ProgrammingJava ProgrammingPortfolio Construction

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData AnalysisRisk ManagementBacktestingScenario AnalysisModel DiagnosticsInvestment StrategiesTest Framework DevelopmentCode QualityModularity

Soft Skills

Analytical MindsetCommunication Skills

Industry Keywords

FinanceQuantitative FinanceFinancial EngineeringAsset AllocationInvestment Frameworks

Tech Stack

Tools & technologies

JavaPython

About the role

Key responsibilities & impact

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

What you’ll need

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).

Benefits

Comp & perks

Competitive salary & truly flexible 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 an ultra-international team (18+ nationalities) spread across our offices in Milan, London and New York.
Annual company retreat at a stunning location.
Fast-track career progression, with opportunities to grow into leadership roles.