Lead of Modeling / Deputy to Head of ML
We are seeking a senior leader to own the Model Layer of our ML-driven quantitative research platform. This role leads architecture design, model development, validation, lifecycle management, and standards for all ML models powering our signal generation pipeline. You will work closely with Quant Research, Feature Engineering, Data Engineering, Trading, and AlgoDev to deliver robust, production-grade predictive models.
What You’ll Do
Lead the design and evolution of the Model Architecture Portfolio across boosting models, time-series deep learning, GNNs, and advanced architectures such as DeepLOB/DeepOB.
Build and maintain leakage-free training pipelines, including IS/OOS splits, walk-forward and rolling validation, and high-quality target engineering.
Define validation protocols (IC/Rank IC, decay, stability) and conduct statistical robustness testing.
Develop explainability and diagnostics frameworks using SHAP, permutation methods, and feature contribution analysis.
Architect ensemble strategies (stacking, blending, regime-switching) and manage routing logic across signals and regimes.
Own monitoring, drift detection, retraining schedules, and overall model lifecycle governance.
Lead and mentor a team of ML researchers and modeling engineers; establish standards for modeling quality, experimentation, and documentation.
Partner cross-functionally to ensure seamless integration of models into production trading systems.
Qualifications
Must-Have Experience
7+ years in machine learning, including 3+ years in quantitative trading or financial ML.
Deep knowledge of ML models.Strong statistical background (bootstrap, t-tests, serial correlation, heteroskedasticity).
Experience building real-time or near-real-time ML systems and pipelines.
Strong understanding of signal validation (IC, Rank IC, decay, cross-sectional behavior).
Solid engineering skills in Python, PyTorch/TF, NumPy, Pandas.
Quant & Market Knowledge
Familiarity with market microstructure, order book data, and factor exposures.
Understanding of PnL decomposition, execution effects, and slippage dynamics.
Leadership & Communication
Experience leading technical teams and driving modeling strategy.
Strong communication, documentation, and cross-functional collaboration skills.
Impact & Scope
This is a high-impact leadership role overseeing critical components of our ML Factory. You will shape modeling strategy, standards, and architecture across the entire research and production pipeline