6 of 6 Remote/Hybrid XGBoost Jobs in the UK excluding London

modelling and applied AI , developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous agent systems ...

modelling and applied AI , developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous agent systems ...

modelling and applied AI, developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous agent systems ...

modelling and applied AI, developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous agent systems ...

with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch. Practical knowledge of algorithms and techniques such as regression, decision trees, random forest, XGBoost, k-means, anomaly detection, and time series forecasting. Working understanding of model evaluation and explainability concepts, e.g. overfitting, bias, cross-validation. Experience developing and implementing ...

underpin your work and help them productionise your applications Preferred Technical Skills Time-series modelling (ARIMA, SARIMA, etc.) and - Tree-based & gradient boosting models (XGBoost, LightGBM, NGBoost) Expertise/knowledge of internally stored data & data consumers as well as other data sources that are currently not databased Python (3+ … SQLAlchemy, Streamlit Infrastructure and DB: Postgres, Warehousing (if we did it), prefect, Kubernetes, SQLAlchemy, AWS Visualisation: Grafana, Superset, Marimo Forecasting + general DS: lightgbm, xgboost, numpy, scipy, scikit-learn Claude AI Ultimately we are looking for someone who is a great fit for our company so we encourage ...