Machine Learning Modeling Lead - DTG Capital Markets - #2112138

Head of Machine Learning Modeling

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.