15 of 15 XGBoost Jobs in London

ready solutions. Strong proficiency in Python and core AI/data science libraries, such as: PyTorch, TensorFlow, ScikitLearn, Keras, NumPy, Pandas PyTorch Geometric, JAX, XGBoost, OpenCV Transformers, LangChain, Pinecone Hands-on experience with cloud computing systems for training, optimising, and deploying models. Strong communication skills and the ability to provide ...

Computer Science, Mathematics, or similar Experience delivering predictive analytics or machine learning solutions Strong skills in Python, SQL, and ML libraries (e.g. scikit-learn, XGBoost, PyTorch, TensorFlow) Hands-on experience with AWS ML services (SageMaker, Lambda, Redshift) Ability to clearly communicate insights to non-technical stakeholders Strong analytical thinking, collaboration ...

understanding of computer science fundamentals and time-series forecasting. Machine Learning: Strong grasp of ML and deep learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, BERT, LSTM, NLP, Transfer Learning). Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community ...

libraries such as Pandas, NumPy, and scikit-learn. Experience with frameworks such as TensorFlow, Keras, or PyTorch. Exposure to gradient boosting tools such as XGBoost, LightGBM, or CatBoost. Experience with model deployment tools (e.g., ONNX, TensorRT, TensorFlow Serving, TorchServe). Familiarity with ML lifecycle tools such as MLflow, Kubeflow ...

should be genuinely strong across most of them and honest about where you want to grow. Supervised & Ensemble Methods. Gradient-boosted trees (XGBoost, LightGBM, CatBoost) for tabular forecasting; understanding of when tree-based models outperform neural approaches on structured data, and vice versa. Strong intuition for regularisation, hyperparameter tuning ...

regulatory and compliance implications in payments Experience working in payments transformation programs Technical Strong Python skills Experience with ML libraries (Scikit-learn, TensorFlow, PyTorch, XGBoost, etc.) Experience with LLMs/GenAI frameworks (LangChain, RAG, prompt engineering, etc.) Experience in cloud (AWS/Azure/GCP) Experience in MLOps tools (MLflow ...

from women who are passionate about machine learning and eager to grow: Strong Python skills and experience with ML libraries (pandas, NumPy, scikit-learn, XGBoost, LightGBM, CatBoost, TensorFlow, Keras, PyTorch). Familiarity with model deployment and serving tools (ONNX, TensorRT, TensorFlow Serving, TorchServe). Experience with ML lifecycle tools (MLflow ...

improvements REQUIREMENTS Strong experience developing credit risk, fraud, or pricing models within financial services or fintech Strong programming experience in Python (pandas, scikit-learn, XGBoost etc.) Solid SQL skills and experience working with large datasets Good understanding of machine learning and statistical modelling techniques HOW TO APPLY Please send your ...

will have experience in many of the following: Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/B testing ...

Machine Learning Strong Understanding of what it actually takes to run ML Systems in Production Hands-On Experience with Deep Learning Frameworks (TensorFlow, PyTorch, XGBoost) Deep Knowledge of Data Warehousing, ETL/ELT Architectures & Heavy Analytic Environments (Apache Beam, Hadoop, Spark, Hive) Responsibilities: Leading Customer-Facing AI Deployments across Europe ...

modern AWS production environments. The Technical Reality: We operate a pragmatic stack where Linear Regression remains vital for stability and baseline performance, while XGBoost and LLMs are used as responsible additions. We are looking for someone who knows when to use a simple linear model and when to deploy … Responsibilities Predictive Modelling (Linear & Non-Linear): You will build and maintain foundational Linear Regression models for credit, affordability, and fraud scoring, while developing advanced XGBoost models for deeper risk insights. You will mine data to find behavioural signals—such as spending volatility or income stability—that predict affordability, repayment ...

Python. • Background in credit risk, rating agency modelling, or customer behaviour modelling. • Confident communicator with senior stakeholders. • Leadership experience in technical teams. • Experience with XGBoost or other boosting techniques. • Knowledge of MLOps or R is a plus but not essential. What They Offer • £120,000 to £150,000 base salary. ...

group with strong influence across risk, product, and strategy. The Role Lead credit decisioning strategy and model development. Stay hands on with modelling using XGBoost, GBM and related techniques. Oversee end-to-end model lifecycle from design to monitoring. Partner with risk, product, and engineering on decisioning and portfolio performance. ...

Science , you will need: • Strong hands on experience building credit or risk models. • Strong experience developing models in python. • Confident with techniques such as XGBoost or GBM. • Ability to link modelling decisions to commercial outcomes. • Clear communication and strong stakeholder management skills being able to manage both upwards and downwards. ...

class classification problems). Work with structured financial transaction data (merchant strings, metadata, timestamps, behavioural features). Apply techniques such as: Gradient boosting (e.g., XGBoost) Tree-based models NLP approaches for merchant text classification Embedding techniques where appropriate Engineer and test new features to improve model accuracy and generalisation. Evaluate … environments. Direct experience working on classification or categorisation problems (ideally transaction, text, or behavioural categorisation). Strong proficiency in Python and ML libraries (e.g., XGBoost, scikit-learn, pandas). Comfortable working with SQL and large datasets (BigQuery experience a strong plus). Experience evaluating model performance rigorously and iterating based ...