At a Glance
- Tasks: Lead the development of cutting-edge machine learning models for trading systems.
- Company: Global quantitative trading firm focused on engineering excellence and innovation.
- Benefits: Remote work, competitive salary, and opportunities for professional growth.
- Other info: Dynamic remote environment with a focus on collaboration and mentorship.
- Why this job: Shape the future of trading with advanced ML techniques and collaborate with top talent.
- Qualifications: 5+ years in machine learning, preferably in finance, with strong Python skills.
The predicted salary is between 80000 - 100000 € per year.
A global quantitative trading organization built around engineering excellence, scientific thinking, and fully automated trading. Our teams create everything in-house—from the research infrastructure to the algorithms that run live in markets around the world. We trade a wide mix of products, including equities, derivatives, options, commodities, rates, and crypto using both high-frequency and mid-frequency strategies. Our dedicated team members are located across multiple continents, and while we maintain physical offices, our workflow is currently designed for a remote environment.
About the Role
We’re hiring an experienced ML leader to guide the next generation of predictive modeling that powers our research and trading systems. In this role, you’ll own the strategy, design, and execution of our modeling framework—from architecture choices to validation standards to production governance. You’ll collaborate closely with quant researchers, data specialists, engineers, and traders to turn cutting-edge research into reliable, high-performance models used in live trading.
Responsibilities
- You’ll be responsible for one of the most critical layers of our research platform—the modeling engine that feeds our trading systems. Your work will influence how we research, validate, and deploy ML-driven signals across the firm.
- Setting the long-term vision for our model portfolio, covering everything from boosted trees to time-series deep learning, graph-based models, and advanced architectures for order-book prediction.
- Designing training pipelines that enforce strict data hygiene—rolling and walk-forward validation, target construction, and leakage-free workflows.
- Building explainability and diagnostic tooling (SHAP, permutation tests, model dissection techniques) to understand model behavior.
- Developing ensemble strategies and regime-aware model routing.
- Leading and mentoring a team of ML researchers, shaping best practices for experimentation and documentation.
- Partnering with engineering and trading teams to ensure smooth deployment of models into live trading systems.
Requirements/Core Experience
- 5+ years working with machine learning, with at least 2 years applying ML in quantitative finance/investments/trading.
- In depth knowledge of modern ML methods and architectures.
- Strong statistical foundation—comfortable with hypothesis testing, bootstrapping, time-series quirks, and related methods.
- Experience building ML systems that operate in real-time or near-real-time environments.
- Strong command of alpha evaluation (IC, rank correlations, stability, decay).
- Proficiency in Python and the scientific/ML ecosystem (NumPy, Pandas, PyTorch/TensorFlow).
- Understanding of market microstructure, order flow, order-book dynamics, and factor behavior is a major plus.
- Experience guiding technical teams and shaping modeling direction.
Machine Learning Modeling Lead - DTG Capital Markets in London employer: DTG Capital Markets
At DTG Capital Markets, we pride ourselves on being a leading global quantitative trading organisation that fosters a culture of engineering excellence and scientific innovation. Our commitment to employee growth is evident through our collaborative environment, where you will work alongside top-tier professionals in machine learning and finance, driving impactful projects that shape the future of trading. With a flexible remote work setup and a focus on cutting-edge technology, we offer a unique opportunity for meaningful contributions in a dynamic and supportive workplace.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Modeling Lead - DTG Capital Markets in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those relevant to finance. We want to see your work in action, so don’t be shy about sharing your GitHub or any live demos.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. We recommend practising common ML interview questions and even doing mock interviews with friends or mentors to build confidence.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Machine Learning Modeling Lead - DTG Capital Markets in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of Machine Learning Modeling Lead. Highlight your experience in quantitative finance and any relevant ML projects you've worked on. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about machine learning and trading. Share specific examples of your past work that demonstrate your expertise and how you can contribute to our team.
Showcase Your Technical Skills:Don’t forget to highlight your technical skills, especially in Python and ML frameworks like PyTorch or TensorFlow. We’re looking for someone who can hit the ground running, so make sure we see your proficiency right away!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people. Good luck!
How to prepare for a job interview at DTG Capital Markets
✨Know Your ML Inside Out
Make sure you’re well-versed in modern machine learning methods and architectures. Brush up on your knowledge of boosted trees, time-series deep learning, and graph-based models. Be ready to discuss how these can be applied in quantitative finance.
✨Showcase Your Real-Time Experience
Since the role involves building ML systems for live trading, prepare examples from your past work where you've successfully implemented real-time or near-real-time ML solutions. Highlight any challenges you faced and how you overcame them.
✨Demonstrate Statistical Savvy
Be prepared to dive into statistical concepts like hypothesis testing and bootstrapping. You might be asked to explain how you would approach model validation and ensure data hygiene in your training pipelines.
✨Collaboration is Key
This role requires working closely with various teams. Think of examples that showcase your ability to collaborate with quant researchers, engineers, and traders. Emphasise your leadership experience and how you’ve mentored others in best practices.
