Machine Leaming Engineer - Applied ML for Trading Signals
New York, New York, United States of America
USD 150K-200K Mid-level Full Time
Tasks
- Apply model explainability tools SHAP feature importance
- Build cross validation frameworks for financial time series purged k fold walk forward
- Develop tree based ensemble models for intraday alpha prediction
- Engineer features from market microstructure order flow imbalance spread dynamics volume patterns cross asset signals
- Implement end to end ML pipelines feature engineering training validation deployment monitoring
- Integrate ML predictions into real time trading engine
- Monitor model performance in production detect drift staleness regime changes
- Optimize low latency model inference for production
- Prototype signals using TabPFN
Perks/Benefits
Skills/Tech-stack
CatBoost | Cross-validation | Feature Selection | Hyperparameter Tuning | LightGBM | Machine Learning | NumPy | Pandas | Polars | Python | SHAP | Scikit-learn | Series analysis | Time Series | Time Series Analysis | Walk Forward Validation | XGBoost
Education
Regions
Countries
States
Cities
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