Senior Quantitative Researcher - AI-Driven Finance & NLP

RavenPack; Amsterdam; On-site; EUR 90,000 - 130,000; Full time

Benefits offered by this job

Relocation assistance

Job summary

RavenPack is seeking a Senior Quantitative Researcher to drive quantitative investment use cases across its product suite. You will lead POC development, guide applied research, and collaborate with enterprise clients to deliver AI-driven finance solutions.

The role requires a strong quantitative finance background and hands-on ML/NLP experience. You will work on alpha generation datasets, time-series workflows, and multi-agent LLM architectures, with relocation support available to move to

Qualifications

• MSc or PhD in Computer Science, Machine Learning, NLP, Quantitative Finance, or related field.
• 3+ years experience in quantitative investment strategies with ML/NLP initiatives.
• Hands-on experience with LLMs, LRMs, and coding assistant technologies.

Responsibilities

• Design and build ML/NLP-powered solutions for alpha generation and financial workflows.
• Engage with clients and partners during POCs and pilots, iterating based on real-world feedback.
• Apply LLM/LRM approaches, fine-tuning, and multi-agent systems to complex investment challenges.
• Stay ahead of AI/ML trends and lead internal R&D aligned with business goals.
• Collaborate with engineers, product managers, and executives to deliver scalable solutions.

Skills

Python

ML/NLP

Time-series modelling

LLMs/LRMs

Client communication

Education

MSc/PhD in CS/ML/NLP/Quantitative Finance

Tools

PyTorch

SQL

Git

Job description

RavenPack is seeking a Senior Quantitative Researcher to drive quantitative investment use cases across its product suite. You will lead POC development, guide applied research, and collaborate with enterprise clients to deliver AI-driven finance solutions.

The role requires a strong quantitative finance background and hands-on ML/NLP experience. You will work on alpha generation datasets, time-series workflows, and multi-agent LLM architectures, with relocation support available to move to