Machine Learning Quant
Da Vinci · Amsterdam, North Holland, Netherlands
- On site
- Full-time
- $150,000 / year
- Amsterdam, North Holland, Netherlands
Job highlights
- Develop and deploy ML/AI models for financial markets.
- Collaborate with research and trading teams.
- Explore cutting-edge ML techniques.
- Own models from research to production.
- Analyze high-frequency data streams.
About the role
About Da Vinci
Da Vinci is a proprietary trading house founded in 2015 and specialized in solving market inefficiencies, identifying opportunities based on volatility arbitrage and delta1 strategies and providing liquidity to the markets. We are headquartered in the home of the world’s first stock market, Amsterdam, and we have offices in Miami, Mumbai and Hong Kong. Today, we trade on the most prominent exchanges across Asia and the US. Our vision is set on sustainable growth and collaboration across teams and offices.About the Role
At Da Vinci Trading, we’re not just building trading systems, we’re building the future of intelligence in the markets. Our teams of researchers, quants, engineers and traders collaborate to push the boundaries of what's possible. If you’re passionate about machine learning, statistical modelling, and want your work to directly impact performance in real‑world financial markets, you’ll feel right at home here.Responsibilities
- Develop, test, and deploy novel ML/AI models for prediction, signal generation, and anomaly detection.
- Work closely with the Quant Research and Trading Intelligence teams to translate insights into live strategies.
- Explore state‑of‑the‑art techniques (e.g., deep learning, reinforcement learning, graph neural networks) and rigorously evaluate their applicability in financial domains.
- Take full ownership of your models and strategies - from signal research, feature engineering, and backtesting through to execution, live performance monitoring, risk assessment, and iterative improvement in production.
- Analyze large, noisy, high‑frequency data streams; performing advanced feature engineering, and bias detection.
- Collaborate with our systems and infrastructure engineers to ensure models are productionised efficiently and reliably.
Requirements
- A strong academic background in Machine Learning, AI, Statistics, Computer Science, Mathematics, or a related field - typically a PhD or equivalent, or an MSc with significant relevant experience
- Hands on experience building and deploying ML/AI models, especially for time series forecasting or anomaly detection.
- Genuine curiosity about trading, market microstructure and financial dynamics
- Proficiency in Python and common ML frameworks (e.g., PyTorch, TensorFlow, scikit‑learn).
- Solid programming and software development skills, with experience in a production environment.
- Experience with core data and infrastructure tools like Docker, S3/MinIO, and PostgreSQL/OLAP databases.
- A deep, intuitive understanding of topics like overfitting, generalization, and feature engineering.
- Stays up to date on ML/AI literature and experiments with new ideas
- The ability to communicate complex ideas clearly and collaborate effectively in a high‑performance team.
Preferred qualifications
- MLOps pipelines and tools (e.g., MLFlow, ClearML, Weights & Biases).
- High-performance computing and GPU optimization (e.g., CUDA, TensorRT).
Benefits
- An opportunity to work beside the best in the field, with direct exposure to live trading - you own your models and strategies end-to-end, from research through to production
- Competitive base salary based on experience
- Excellent variable pay and growth opportunities
- Outstanding performance is also rewarded with shareholding in the company
- A relocation package when moving from abroad, including a relocation budget, flight coverage, house-finding service and expat support
- Meals during work hours
- Social events and after-work drinks
- Reimbursement of travel costs
- Access to the in-house gym and chair massage
- In-house game room (pool table, board games and console games)
Key skills/competency
- Machine Learning
- Quantitative Analysis
- Python
- Deep Learning
- Reinforcement Learning
- Time Series Forecasting
- Anomaly Detection
- Feature Engineering
- Model Deployment
- Financial Markets
Skills & topics
- Machine Learning
- Quant
- Python
- AI
- Deep Learning
- Time Series Forecasting
- Anomaly Detection
- Feature Engineering
- Quantitative Finance
- Trading
How to get hired
- Tailor your resume: Highlight Machine Learning, AI, Python, and financial domain experience.
- Showcase projects: Detail your experience with model deployment and production environments.
- Demonstrate curiosity: Express genuine interest in trading and market microstructure.
- Prepare for technicals: Be ready to discuss ML concepts and coding challenges.
- Network effectively: Connect with current employees on LinkedIn for insights.
Technical preparation
Master Python and ML libraries.,Practice time series forecasting.,Understand model deployment tools.,Study anomaly detection techniques.
Behavioral questions
Describe a complex ML problem you solved.,How do you handle noisy data?,Explain your approach to model ownership.,How do you collaborate with engineers?
Frequently asked questions
- What is the typical academic background for a Machine Learning Quant at Da Vinci?
- Da Vinci typically looks for candidates with a strong academic background in fields like Machine Learning, AI, Statistics, Computer Science, or Mathematics. A PhD or an MSc with significant relevant experience is generally expected for this Machine Learning Quant role.
- What programming languages and ML frameworks are essential for this Machine Learning Quant position?
- Proficiency in Python is essential for this Machine Learning Quant role. Familiarity with common ML frameworks such as PyTorch, TensorFlow, and scikit-learn is also a requirement.
- Does Da Vinci require prior experience in financial markets for the Machine Learning Quant role?
- While not always mandatory, a genuine curiosity about trading, market microstructure, and financial dynamics is highly valued. Previous hands-on experience building and deploying ML/AI models in a production environment, especially for time series forecasting or anomaly detection, is crucial for this Machine Learning Quant position.
- What kind of data will a Machine Learning Quant work with at Da Vinci?
- As a Machine Learning Quant at Da Vinci, you will analyze large, noisy, high-frequency data streams. This involves advanced feature engineering and bias detection, directly impacting live trading strategies.
- What are the career growth opportunities for a Machine Learning Quant at Da Vinci?
- Da Vinci offers excellent variable pay and growth opportunities for its Machine Learning Quant hires. Outstanding performance can be rewarded with shareholding in the company, providing a significant growth path.
- Does Da Vinci offer support for relocating to Amsterdam for the Machine Learning Quant role?
- Yes, Da Vinci provides a comprehensive relocation package for international hires, including a relocation budget, flight coverage, a house-finding service, and expat support for those moving to Amsterdam for the Machine Learning Quant position.
- What is the expected timeline for hearing back after applying for the Machine Learning Quant role?
- Da Vinci aims to get back to all applicants by May 27th. This allows ample time for reviewing applications for the Machine Learning Quant position.