Quantitative Researcher - Cross-Asset, Deep Learning

JR France; Paris; Sur place; EUR 60 000 - 100 000; Plein temps

Résumé du poste

A leading quant trading firm in Paris is seeking a Quantitative Researcher specializing in Cross-Asset and Deep Learning. This role involves developing machine learning models for alpha extraction and pricing across non-equity markets, offering competitive compensation and opportunities for career advancement.

Prestations

Competitive compensation

Career development opportunities

Access to advanced ML resources

Collaborate with top talent

Qualifications

• 2-7 years in quantitative research with a focus on deep learning applications.
• Strong experience in non-equity asset classes and cross-asset research.
• Proficiency in deep learning frameworks and quantitative modeling.

Responsabilités

• Design and deploy advanced deep learning models for non-equity asset classes.
• Innovate with alternative data sources for signal extraction and pricing.
• Conduct research to develop scalable ML models for cross-asset strategies.

Connaissances

Deep Learning

Quantitative Research

Machine Learning

Data Processing

Description du poste

Social network you want to login/join with:

Quantitative Researcher - Cross-Asset, Deep Learning, paris

col-narrow-left

Client:

CW Talent Solutions

Location:

paris, France

Job Category:

Other

-

EU work permit required:

Yes

col-narrow-right

Job Reference:

137075731094254387232761

Job Views:

2

Posted:

24.05.2025

Expiry Date:

08.07.2025

col-wide

Job Description:

Quantitative Researcher – Cross-Asset, Deep Learning

CW Talent Solutions is excited to represent a leading quant trading firm in Paris looking to add a Quantitative Researcher with a focus on Cross-Asset and Deep Learning. This role offers a unique chance to apply advanced deep learning techniques to develop and deploy ML models for alpha extraction, pricing, and volume management across non-equity markets.

The Firm:

• Global Quant Trading Leader specializing in cross-asset, non-equity strategies
• Known for leveraging cutting-edge technology and deep learning for high-performance results
• Data-centric approach focused on sustainable alpha generation and capital efficiency
• Collaborative and research-driven culture that values continuous innovation

The Role:

Seeking Quantitative Researchers with expertise in Cross-Asset and Deep Learning for Non-Equity markets

Develop machine learning models to interpret alpha signals from alternative data, optimize pricing, and manage trade volume and flow

Key Responsibilities:

• Design and deploy advanced deep learning models to interpret signals in non-equity asset classes
• Innovate with alternative data sources for signal extraction, pricing, and flow management
• Conduct research to develop scalable ML models for cross-asset strategies, optimizing trade volume and improving alpha generation
• Collaborate within a high-performing team, contributing to impactful model development and deployment
• Ensure adherence to industry standards and regulatory requirements

Preferred Experience:

• 2-7 years in quantitative research with a focus on deep learning applications
• Strong experience in non-equity asset classes and cross-asset research
• Proficiency in deep learning frameworks, data processing, and quantitative modeling
• Background in utilizing alternative data for trading insights and signal interpretation
• Analytical and innovative mindset with a commitment to rigorous research

What’s in it for you?

• Competitive compensation and career development opportunities
• Access to advanced ML and deep learning resources for quantitative research
• Join a pioneering firm in Paris where quantitative and ML research are core to strategy
• Collaborate with top talent in a firm dedicated to data-driven market solutions

Why Join Us?

Our clients stand out in the quant industry for their focus on non-equity strategies and deep learning innovation. If you are passionate about applying ML in complex financial contexts and making a tangible impact, this could be the role for you.